Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -0,0 +1,485 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:118400
+- loss:TripletLoss
+base_model: DeepChem/ChemBERTa-77M-MLM
+widget:
+- source_sentence: CC(C)C1CCC(C(=O)NC(Cc2ccccc2)C(=O)[O-])CC1
+  sentences:
+  - C[NH2+]CCCC1c2ccccc2C=Cc2ccccc21
+  - COC(=O)NC(C(=O)NC(Cc1ccccc1)C(O)CN(Cc1ccc(-c2ccccn2)cc1)NC(=O)C(NC(=O)OC)C(C)(C)C)C(C)(C)C
+  - CC1C=CC=CCCC=CC=CC=CC=CC(OC2OC(C)C(O)C([NH3+])C2O)CC(O)C(C(=O)[O-])C(O)CC(=O)CC(O)C(O)CCC(O)CC(O)CC(O)CC(=O)OC(C)C(C)C1O
+- source_sentence: C[NH+]1CCCC1Cc1c[nH]c2ccc(CCS(=O)(=O)c3ccccc3)cc12
+  sentences:
+  - CC(C)CC([NH+](C)C)C1(c2ccc(Cl)cc2)CCC1
+  - CC(C)CNCc1ccc(-c2ccccc2S(=O)(=O)N2CCCC2)cc1
+  - CC(Oc1cc(-c2cnn(C3CC[NH2+]CC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl
+- source_sentence: C[NH+]1C2CCC1CC(OC(c1ccccc1)c1ccccc1)C2
+  sentences:
+  - C[NH2+]C1C(O)C([NH2+]C)C2OC3(O)C(=O)CC(C)OC3OC2C1O
+  - C=CC1(C)CC(OC(=O)CSC2CC3CCC(C2)[NH+]3C)C2(C)C(C)CCC3(CCC(=O)C32)C(C)C1O
+  - CC(C)CC(NC(=O)C(CCc1ccccc1)NC(=O)CN1CCOCC1)C(=O)NC(Cc1ccccc1)C(=O)NC(CC(C)C)C(=O)C1(C)CO1
+- source_sentence: CC(C)CC(NC(=O)C(Cc1ccc2ccccc2c1)NC(=O)C(Cc1ccc(O)cc1)NC(=O)C(CO)NC(=O)C(Cc1c[nH]c2ccccc12)NC(=O)C(Cc1c[nH]cn1)NC(=O)C1CCC(=O)N1)C(=O)NC(CCCNC(N)=[NH2+])C(=O)N1CCCC1C(=O)NCC(N)=O
+  sentences:
+  - C[NH2+]C1CCC(c2ccc(Cl)c(Cl)c2)c2ccccc21
+  - C=C1CC2CCC34CC5OC6C(OC7CCC(CC(=O)CC8C(CC9OC(CCC1O2)CC(C)C9=C)OC(CC(O)CN)C8OC)OC7C6O3)C5O4
+  - C[N+]1(C)CCC(=C(c2ccccc2)c2ccccc2)CC1
+- source_sentence: CON=C(C(=O)NC1C(=O)N2C(C(=O)[O-])=C(C[N+]3(C)CCCC3)CSC12)c1csc(N)n1
+  sentences:
+  - CC1CNc2c(cccc2S(=O)(=O)NC(CCC[NH+]=C(N)N)C(=O)N2CCC(C)CC2C(=O)[O-])C1
+  - CC1C=CC=CCCC=CC=CC=CC=CC(OC2OC(C)C(O)C([NH3+])C2O)CC(O)C(C(=O)[O-])C(O)CC(=O)CC(O)C(O)CCC(O)CC(O)CC(O)CC(=O)OC(C)C(C)C1O
+  - CC(C)C1(C(=O)NC2CC(=O)OC2(O)CF)CC(c2nccc3ccccc23)=NO1
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- cosine_accuracy
+model-index:
+- name: SentenceTransformer based on DeepChem/ChemBERTa-77M-MLM
+  results:
+  - task:
+      type: triplet
+      name: Triplet
+    dataset:
+      name: all dev
+      type: all-dev
+    metrics:
+    - type: cosine_accuracy
+      value: 0.7135134935379028
+      name: Cosine Accuracy
+---
+
+# SentenceTransformer based on DeepChem/ChemBERTa-77M-MLM
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [DeepChem/ChemBERTa-77M-MLM](https://huggingface.co/DeepChem/ChemBERTa-77M-MLM). It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [DeepChem/ChemBERTa-77M-MLM](https://huggingface.co/DeepChem/ChemBERTa-77M-MLM) <!-- at revision ed8a5374f2024ec8da53760af91a33fb8f6a15ff -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 384 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: RobertaModel 
+  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("HassanCS/chemBERTa-tuned-on-ClinTox-using-MultipleNegativesRankingLoss")
+# Run inference
+sentences = [
+    'CON=C(C(=O)NC1C(=O)N2C(C(=O)[O-])=C(C[N+]3(C)CCCC3)CSC12)c1csc(N)n1',
+    'CC1CNc2c(cccc2S(=O)(=O)NC(CCC[NH+]=C(N)N)C(=O)N2CCC(C)CC2C(=O)[O-])C1',
+    'CC(C)C1(C(=O)NC2CC(=O)OC2(O)CF)CC(c2nccc3ccccc23)=NO1',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 384]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Triplet
+
+* Dataset: `all-dev`
+* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
+
+| Metric              | Value      |
+|:--------------------|:-----------|
+| **cosine_accuracy** | **0.7135** |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 118,400 training samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                            | positive                                                                           | negative                                                                           |
+  |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                             | string                                                                             |
+  | details | <ul><li>min: 20 tokens</li><li>mean: 33.0 tokens</li><li>max: 60 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 47.34 tokens</li><li>max: 212 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 53.88 tokens</li><li>max: 212 tokens</li></ul> |
+* Samples:
+  | anchor                                                 | positive                                                                                     | negative                                             |
+  |:-------------------------------------------------------|:---------------------------------------------------------------------------------------------|:-----------------------------------------------------|
+  | <code>CC(C)CC(NC(=O)CNC(=O)c1cc(Cl)ccc1Cl)B(O)O</code> | <code>CC(=O)OC1CCC2(C)C(=CCC3C2CCC2(C)C(c4cccnc4)=CCC32)C1</code>                            | <code>CCOC(=O)c1ncn2c1CN(C)C(=O)c1cc(F)ccc1-2</code> |
+  | <code>CC(C)CC(NC(=O)CNC(=O)c1cc(Cl)ccc1Cl)B(O)O</code> | <code>COc1ccc(C(CN(C)C)C2(O)CCCCC2)cc1</code>                                                | <code>C[NH2+]C1(C)C2CCC(C2)C1(C)C</code>             |
+  | <code>CC(C)CC(NC(=O)CNC(=O)c1cc(Cl)ccc1Cl)B(O)O</code> | <code>CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1.Cc1ccc(S(=O)(=O)O)cc1</code> | <code>Nc1ncnc2c1ncn2C1OC(CO)C(O)C1O</code>           |
+* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
+  ```json
+  {
+      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
+      "triplet_margin": 5
+  }
+  ```
+
+### Evaluation Dataset
+
+#### Unnamed Dataset
+
+* Size: 1,480 evaluation samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | anchor                                                                              | positive                                                                           | negative                                                                            |
+  |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                              | string                                                                             | string                                                                              |
+  | details | <ul><li>min: 18 tokens</li><li>mean: 54.07 tokens</li><li>max: 169 tokens</li></ul> | <ul><li>min: 18 tokens</li><li>mean: 60.4 tokens</li><li>max: 244 tokens</li></ul> | <ul><li>min: 30 tokens</li><li>mean: 71.25 tokens</li><li>max: 141 tokens</li></ul> |
+* Samples:
+  | anchor                                                                  | positive                                                    | negative                                                                 |
+  |:------------------------------------------------------------------------|:------------------------------------------------------------|:-------------------------------------------------------------------------|
+  | <code>CC(C)OC(=O)CCCC=CCC1C(O)CC(O)C1C=CC(O)COc1cccc(C(F)(F)F)c1</code> | <code>CC12CCCCCC(Cc3ccc(O)cc31)C2[NH3+]</code>              | <code>CC(C)C(CN1CCC(C)(c2cccc(O)c2)C(C)C1)NC(=O)C1Cc2ccc(O)cc2CN1</code> |
+  | <code>CC(C)OC(=O)CCCC=CCC1C(O)CC(O)C1C=CC(O)COc1cccc(C(F)(F)F)c1</code> | <code>COc1cc2c(cc1OC)C1CC(=O)C(CC(C)C)C[NH+]1CC2</code>     | <code>CC(C)C(CN1CCC(C)(c2cccc(O)c2)C(C)C1)NC(=O)C1Cc2ccc(O)cc2CN1</code> |
+  | <code>CC(C)OC(=O)CCCC=CCC1C(O)CC(O)C1C=CC(O)COc1cccc(C(F)(F)F)c1</code> | <code>C[NH+](C)CCC=C1c2ccccc2COc2ccc(CC(=O)[O-])cc21</code> | <code>CC(C)C1(C(=O)NC2CC(=O)OC2(O)CF)CC(c2nccc3ccccc23)=NO1</code>       |
+* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
+  ```json
+  {
+      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
+      "triplet_margin": 5
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 5
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 5
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+| Epoch  | Step  | Training Loss | Validation Loss | all-dev_cosine_accuracy |
+|:------:|:-----:|:-------------:|:---------------:|:-----------------------:|
+| 0.0676 | 500   | 5.0821        | 5.1737          | 0.4047                  |
+| 0.1351 | 1000  | 4.9869        | 5.1766          | 0.4230                  |
+| 0.2027 | 1500  | 4.5562        | 4.9102          | 0.5345                  |
+| 0.2703 | 2000  | 3.2364        | 4.3712          | 0.6534                  |
+| 0.3378 | 2500  | 2.0738        | 4.0704          | 0.6736                  |
+| 0.4054 | 3000  | 1.4239        | 4.0200          | 0.6635                  |
+| 0.4730 | 3500  | 1.1578        | 3.7202          | 0.6791                  |
+| 0.5405 | 4000  | 0.9669        | 3.7197          | 0.6831                  |
+| 0.6081 | 4500  | 0.714         | 3.8818          | 0.6547                  |
+| 0.6757 | 5000  | 0.5359        | 4.0987          | 0.6243                  |
+| 0.7432 | 5500  | 0.5663        | 3.8127          | 0.6500                  |
+| 0.8108 | 6000  | 0.4827        | 3.8346          | 0.6676                  |
+| 0.8784 | 6500  | 0.4758        | 3.8333          | 0.6507                  |
+| 0.9459 | 7000  | 0.4759        | 3.6872          | 0.6912                  |
+| 1.0135 | 7500  | 0.4651        | 3.7229          | 0.6831                  |
+| 1.0811 | 8000  | 0.4739        | 3.8041          | 0.6662                  |
+| 1.1486 | 8500  | 0.4458        | 3.8235          | 0.6703                  |
+| 1.2162 | 9000  | 0.4189        | 3.7957          | 0.6716                  |
+| 1.2838 | 9500  | 0.4504        | 3.7422          | 0.6784                  |
+| 1.3514 | 10000 | 0.413         | 3.7588          | 0.6770                  |
+| 1.4189 | 10500 | 0.3808        | 3.9750          | 0.6615                  |
+| 1.4865 | 11000 | 0.3853        | 3.7417          | 0.6953                  |
+| 1.5541 | 11500 | 0.379         | 3.7319          | 0.6993                  |
+| 1.6216 | 12000 | 0.429         | 3.5620          | 0.7209                  |
+| 1.6892 | 12500 | 0.3735        | 3.6900          | 0.7020                  |
+| 1.7568 | 13000 | 0.3908        | 3.8182          | 0.6932                  |
+| 1.8243 | 13500 | 0.3848        | 3.7228          | 0.7101                  |
+| 1.8919 | 14000 | 0.3777        | 3.6604          | 0.7149                  |
+| 1.9595 | 14500 | 0.3912        | 3.7849          | 0.6946                  |
+| 2.0269 | 15000 | 0.3282        | 3.8607          | 0.7014                  |
+| 2.0945 | 15500 | 0.3324        | 3.8573          | 0.6953                  |
+| 2.1620 | 16000 | 0.3852        | 3.9420          | 0.7000                  |
+| 2.2296 | 16500 | 0.3633        | 3.7928          | 0.7189                  |
+| 2.2972 | 17000 | 0.3493        | 3.8217          | 0.7216                  |
+| 2.3647 | 17500 | 0.3554        | 3.8546          | 0.6993                  |
+| 2.4323 | 18000 | 0.3363        | 3.7764          | 0.6993                  |
+| 2.4999 | 18500 | 0.377         | 3.8224          | 0.6959                  |
+| 2.5674 | 19000 | 0.3569        | 3.8376          | 0.7155                  |
+| 2.635  | 19500 | 0.3414        | 4.0017          | 0.7034                  |
+| 2.7026 | 20000 | 0.3567        | 3.7405          | 0.7135                  |
+| 2.7701 | 20500 | 0.3524        | 3.9446          | 0.7189                  |
+| 2.8377 | 21000 | 0.3347        | 3.8140          | 0.7169                  |
+| 2.9053 | 21500 | 0.3458        | 4.0700          | 0.7088                  |
+| 2.9728 | 22000 | 0.3632        | 3.7930          | 0.7081                  |
+| 3.0404 | 22500 | 0.3496        | 3.9884          | 0.7236                  |
+| 3.1080 | 23000 | 0.3426        | 3.7102          | 0.7155                  |
+| 3.1755 | 23500 | 0.3579        | 3.9201          | 0.7135                  |
+| 3.2431 | 24000 | 0.3553        | 4.2237          | 0.7270                  |
+| 3.3107 | 24500 | 0.345         | 3.8090          | 0.7189                  |
+| 3.3782 | 25000 | 0.3475        | 3.7802          | 0.7284                  |
+| 3.4458 | 25500 | 0.3326        | 3.7549          | 0.7250                  |
+| 3.5134 | 26000 | 0.3228        | 3.6717          | 0.7216                  |
+| 3.5809 | 26500 | 0.3311        | 3.8241          | 0.7155                  |
+| 3.6485 | 27000 | 0.3215        | 3.8151          | 0.7142                  |
+| 3.7161 | 27500 | 0.3534        | 3.8639          | 0.7149                  |
+| 3.7836 | 28000 | 0.3369        | 4.0947          | 0.7101                  |
+| 3.8512 | 28500 | 0.3229        | 4.0495          | 0.7101                  |
+| 3.9188 | 29000 | 0.3442        | 4.0408          | 0.7169                  |
+| 3.9864 | 29500 | 0.3059        | 3.9493          | 0.6959                  |
+| 4.0538 | 30000 | 0.3349        | 4.0431          | 0.7108                  |
+| 4.1214 | 30500 | 0.3266        | 4.0224          | 0.7189                  |
+| 4.1889 | 31000 | 0.3501        | 3.9502          | 0.7169                  |
+| 4.2565 | 31500 | 0.3676        | 3.8903          | 0.7196                  |
+| 4.3241 | 32000 | 0.3191        | 3.7994          | 0.7162                  |
+| 4.3916 | 32500 | 0.3317        | 3.7889          | 0.7182                  |
+| 4.4592 | 33000 | 0.3304        | 3.8661          | 0.7108                  |
+| 4.5268 | 33500 | 0.3332        | 3.8822          | 0.7115                  |
+| 4.5943 | 34000 | 0.3435        | 3.7945          | 0.7088                  |
+| 4.6619 | 34500 | 0.317         | 3.8721          | 0.7243                  |
+| 4.7295 | 35000 | 0.3038        | 3.8615          | 0.7209                  |
+| 4.7970 | 35500 | 0.3093        | 3.8360          | 0.7162                  |
+| 4.8646 | 36000 | 0.3309        | 3.8277          | 0.7155                  |
+| 4.9322 | 36500 | 0.3378        | 3.7988          | 0.7128                  |
+| 4.9997 | 37000 | 0.311         | 3.8015          | 0.7135                  |
+
+
+### Framework Versions
+- Python: 3.11.11
+- Sentence Transformers: 3.4.1
+- Transformers: 4.47.1
+- PyTorch: 2.5.1+cu124
+- Accelerate: 1.2.1
+- Datasets: 3.2.0
+- Tokenizers: 0.21.0
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### TripletLoss
+```bibtex
+@misc{hermans2017defense,
+    title={In Defense of the Triplet Loss for Person Re-Identification},
+    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
+    year={2017},
+    eprint={1703.07737},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

added_tokens.json

@@ -0,0 +1,4 @@
+{
+  "</s>": 592,
+  "<s>": 591
+}

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "DeepChem/ChemBERTa-77M-MLM",
+  "architectures": [
+    "RobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.109,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.144,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 464,
+  "is_gpu": true,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 515,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 3,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 600
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.4.1",
+    "transformers": "4.47.1",
+    "pytorch": "2.5.1+cu124"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

merges.txt

@@ -0,0 +1 @@
+#version: 0.2

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db59b3c1992909fd850d296a0ed49b40978771e008e8f437a74d46bde7cafac2
+size 13715688

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,712 @@
+{
+  "version": "1.0",
+  "truncation": {
+    "direction": "Right",
+    "max_length": 512,
+    "strategy": "LongestFirst",
+    "stride": 0
+  },
+  "padding": {
+    "strategy": "BatchLongest",
+    "direction": "Right",
+    "pad_to_multiple_of": null,
+    "pad_id": 0,
+    "pad_type_id": 0,
+    "pad_token": "[PAD]"
+  },
+  "added_tokens": [
+    {
+      "id": 0,
+      "content": "[PAD]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 11,
+      "content": "[UNK]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 12,
+      "content": "[CLS]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 13,
+      "content": "[SEP]",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 14,
+      "content": "[MASK]",
+      "single_word": false,
+      "lstrip": true,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    {
+      "id": 591,
+      "content": "<s>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": true,
+      "special": true
+    },
+    {
+      "id": 592,
+      "content": "</s>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": true,
+      "special": true
+    }
+  ],
+  "normalizer": null,
+  "pre_tokenizer": {
+    "type": "ByteLevel",
+    "add_prefix_space": false,
+    "trim_offsets": true,
+    "use_regex": true
+  },
+  "post_processor": {
+    "type": "RobertaProcessing",
+    "sep": [
+      "[SEP]",
+      13
+    ],
+    "cls": [
+      "[CLS]",
+      12
+    ],
+    "trim_offsets": true,
+    "add_prefix_space": false
+  },
+  "decoder": {
+    "type": "ByteLevel",
+    "add_prefix_space": true,
+    "trim_offsets": true,
+    "use_regex": true
+  },
+  "model": {
+    "type": "BPE",
+    "dropout": null,
+    "unk_token": null,
+    "continuing_subword_prefix": "",
+    "end_of_word_suffix": "",
+    "fuse_unk": false,
+    "byte_fallback": false,
+    "ignore_merges": false,
+    "vocab": {
+      "[PAD]": 0,
+      "[unused1]": 1,
+      "[unused2]": 2,
+      "[unused3]": 3,
+      "[unused4]": 4,
+      "[unused5]": 5,
+      "[unused6]": 6,
+      "[unused7]": 7,
+      "[unused8]": 8,
+      "[unused9]": 9,
+      "[unused10]": 10,
+      "[UNK]": 11,
+      "[CLS]": 12,
+      "[SEP]": 13,
+      "[MASK]": 14,
+      "c": 15,
+      "C": 16,
+      "(": 17,
+      ")": 18,
+      "O": 19,
+      "1": 20,
+      "2": 21,
+      "=": 22,
+      "N": 23,
+      ".": 24,
+      "n": 25,
+      "3": 26,
+      "F": 27,
+      "Cl": 28,
+      ">>": 29,
+      "~": 30,
+      "-": 31,
+      "4": 32,
+      "[C@H]": 33,
+      "S": 34,
+      "[C@@H]": 35,
+      "[O-]": 36,
+      "Br": 37,
+      "#": 38,
+      "/": 39,
+      "[nH]": 40,
+      "[N+]": 41,
+      "s": 42,
+      "5": 43,
+      "o": 44,
+      "P": 45,
+      "[Na+]": 46,
+      "[Si]": 47,
+      "I": 48,
+      "[Na]": 49,
+      "[Pd]": 50,
+      "[K+]": 51,
+      "[K]": 52,
+      "[P]": 53,
+      "B": 54,
+      "[C@]": 55,
+      "[C@@]": 56,
+      "[Cl-]": 57,
+      "6": 58,
+      "[OH-]": 59,
+      "\\": 60,
+      "[N-]": 61,
+      "[Li]": 62,
+      "[H]": 63,
+      "[2H]": 64,
+      "[NH4+]": 65,
+      "[c-]": 66,
+      "[P-]": 67,
+      "[Cs+]": 68,
+      "[Li+]": 69,
+      "[Cs]": 70,
+      "[NaH]": 71,
+      "[H-]": 72,
+      "[O+]": 73,
+      "[BH4-]": 74,
+      "[Cu]": 75,
+      "7": 76,
+      "[Mg]": 77,
+      "[Fe+2]": 78,
+      "[n+]": 79,
+      "[Sn]": 80,
+      "[BH-]": 81,
+      "[Pd+2]": 82,
+      "[CH]": 83,
+      "[I-]": 84,
+      "[Br-]": 85,
+      "[C-]": 86,
+      "[Zn]": 87,
+      "[B-]": 88,
+      "[F-]": 89,
+      "[Al]": 90,
+      "[P+]": 91,
+      "[BH3-]": 92,
+      "[Fe]": 93,
+      "[C]": 94,
+      "[AlH4]": 95,
+      "[Ni]": 96,
+      "[SiH]": 97,
+      "8": 98,
+      "[Cu+2]": 99,
+      "[Mn]": 100,
+      "[AlH]": 101,
+      "[nH+]": 102,
+      "[AlH4-]": 103,
+      "[O-2]": 104,
+      "[Cr]": 105,
+      "[Mg+2]": 106,
+      "[NH3+]": 107,
+      "[S@]": 108,
+      "[Pt]": 109,
+      "[Al+3]": 110,
+      "[S@@]": 111,
+      "[S-]": 112,
+      "[Ti]": 113,
+      "[Zn+2]": 114,
+      "[PH]": 115,
+      "[NH2+]": 116,
+      "[Ru]": 117,
+      "[Ag+]": 118,
+      "[S+]": 119,
+      "[I+3]": 120,
+      "[NH+]": 121,
+      "[Ca+2]": 122,
+      "[Ag]": 123,
+      "9": 124,
+      "[Os]": 125,
+      "[Se]": 126,
+      "[SiH2]": 127,
+      "[Ca]": 128,
+      "[Ti+4]": 129,
+      "[Ac]": 130,
+      "[Cu+]": 131,
+      "[S]": 132,
+      "[Rh]": 133,
+      "[Cl+3]": 134,
+      "[cH-]": 135,
+      "[Zn+]": 136,
+      "[O]": 137,
+      "[Cl+]": 138,
+      "[SH]": 139,
+      "[H+]": 140,
+      "[Pd+]": 141,
+      "[se]": 142,
+      "[PH+]": 143,
+      "[I]": 144,
+      "[Pt+2]": 145,
+      "[C+]": 146,
+      "[Mg+]": 147,
+      "[Hg]": 148,
+      "[W]": 149,
+      "[SnH]": 150,
+      "[SiH3]": 151,
+      "[Fe+3]": 152,
+      "[NH]": 153,
+      "[Mo]": 154,
+      "[CH2+]": 155,
+      "%10": 156,
+      "[CH2-]": 157,
+      "[CH2]": 158,
+      "[n-]": 159,
+      "[Ce+4]": 160,
+      "[NH-]": 161,
+      "[Co]": 162,
+      "[I+]": 163,
+      "[PH2]": 164,
+      "[Pt+4]": 165,
+      "[Ce]": 166,
+      "[B]": 167,
+      "[Sn+2]": 168,
+      "[Ba+2]": 169,
+      "%11": 170,
+      "[Fe-3]": 171,
+      "[18F]": 172,
+      "[SH-]": 173,
+      "[Pb+2]": 174,
+      "[Os-2]": 175,
+      "[Zr+4]": 176,
+      "[N]": 177,
+      "[Ir]": 178,
+      "[Bi]": 179,
+      "[Ni+2]": 180,
+      "[P@]": 181,
+      "[Co+2]": 182,
+      "[s+]": 183,
+      "[As]": 184,
+      "[P+3]": 185,
+      "[Hg+2]": 186,
+      "[Yb+3]": 187,
+      "[CH-]": 188,
+      "[Zr+2]": 189,
+      "[Mn+2]": 190,
+      "[CH+]": 191,
+      "[In]": 192,
+      "[KH]": 193,
+      "[Ce+3]": 194,
+      "[Zr]": 195,
+      "[AlH2-]": 196,
+      "[OH2+]": 197,
+      "[Ti+3]": 198,
+      "[Rh+2]": 199,
+      "[Sb]": 200,
+      "[S-2]": 201,
+      "%12": 202,
+      "[P@@]": 203,
+      "[Si@H]": 204,
+      "[Mn+4]": 205,
+      "p": 206,
+      "[Ba]": 207,
+      "[NH2-]": 208,
+      "[Ge]": 209,
+      "[Pb+4]": 210,
+      "[Cr+3]": 211,
+      "[Au]": 212,
+      "[LiH]": 213,
+      "[Sc+3]": 214,
+      "[o+]": 215,
+      "[Rh-3]": 216,
+      "%13": 217,
+      "[Br]": 218,
+      "[Sb-]": 219,
+      "[S@+]": 220,
+      "[I+2]": 221,
+      "[Ar]": 222,
+      "[V]": 223,
+      "[Cu-]": 224,
+      "[Al-]": 225,
+      "[Te]": 226,
+      "[13c]": 227,
+      "[13C]": 228,
+      "[Cl]": 229,
+      "[PH4+]": 230,
+      "[SiH4]": 231,
+      "[te]": 232,
+      "[CH3-]": 233,
+      "[S@@+]": 234,
+      "[Rh+3]": 235,
+      "[SH+]": 236,
+      "[Bi+3]": 237,
+      "[Br+2]": 238,
+      "[La]": 239,
+      "[La+3]": 240,
+      "[Pt-2]": 241,
+      "[N@@]": 242,
+      "[PH3+]": 243,
+      "[N@]": 244,
+      "[Si+4]": 245,
+      "[Sr+2]": 246,
+      "[Al+]": 247,
+      "[Pb]": 248,
+      "[SeH]": 249,
+      "[Si-]": 250,
+      "[V+5]": 251,
+      "[Y+3]": 252,
+      "[Re]": 253,
+      "[Ru+]": 254,
+      "[Sm]": 255,
+      "*": 256,
+      "[3H]": 257,
+      "[NH2]": 258,
+      "[Ag-]": 259,
+      "[13CH3]": 260,
+      "[OH+]": 261,
+      "[Ru+3]": 262,
+      "[OH]": 263,
+      "[Gd+3]": 264,
+      "[13CH2]": 265,
+      "[In+3]": 266,
+      "[Si@@]": 267,
+      "[Si@]": 268,
+      "[Ti+2]": 269,
+      "[Sn+]": 270,
+      "[Cl+2]": 271,
+      "[AlH-]": 272,
+      "[Pd-2]": 273,
+      "[SnH3]": 274,
+      "[B+3]": 275,
+      "[Cu-2]": 276,
+      "[Nd+3]": 277,
+      "[Pb+3]": 278,
+      "[13cH]": 279,
+      "[Fe-4]": 280,
+      "[Ga]": 281,
+      "[Sn+4]": 282,
+      "[Hg+]": 283,
+      "[11CH3]": 284,
+      "[Hf]": 285,
+      "[Pr]": 286,
+      "[Y]": 287,
+      "[S+2]": 288,
+      "[Cd]": 289,
+      "[Cr+6]": 290,
+      "[Zr+3]": 291,
+      "[Rh+]": 292,
+      "[CH3]": 293,
+      "[N-3]": 294,
+      "[Hf+2]": 295,
+      "[Th]": 296,
+      "[Sb+3]": 297,
+      "%14": 298,
+      "[Cr+2]": 299,
+      "[Ru+2]": 300,
+      "[Hf+4]": 301,
+      "[14C]": 302,
+      "[Ta]": 303,
+      "[Tl+]": 304,
+      "[B+]": 305,
+      "[Os+4]": 306,
+      "[PdH2]": 307,
+      "[Pd-]": 308,
+      "[Cd+2]": 309,
+      "[Co+3]": 310,
+      "[S+4]": 311,
+      "[Nb+5]": 312,
+      "[123I]": 313,
+      "[c+]": 314,
+      "[Rb+]": 315,
+      "[V+2]": 316,
+      "[CH3+]": 317,
+      "[Ag+2]": 318,
+      "[cH+]": 319,
+      "[Mn+3]": 320,
+      "[Se-]": 321,
+      "[As-]": 322,
+      "[Eu+3]": 323,
+      "[SH2]": 324,
+      "[Sm+3]": 325,
+      "[IH+]": 326,
+      "%15": 327,
+      "[OH3+]": 328,
+      "[PH3]": 329,
+      "[IH2+]": 330,
+      "[SH2+]": 331,
+      "[Ir+3]": 332,
+      "[AlH3]": 333,
+      "[Sc]": 334,
+      "[Yb]": 335,
+      "[15NH2]": 336,
+      "[Lu]": 337,
+      "[sH+]": 338,
+      "[Gd]": 339,
+      "[18F-]": 340,
+      "[SH3+]": 341,
+      "[SnH4]": 342,
+      "[TeH]": 343,
+      "[Si@@H]": 344,
+      "[Ga+3]": 345,
+      "[CaH2]": 346,
+      "[Tl]": 347,
+      "[Ta+5]": 348,
+      "[GeH]": 349,
+      "[Br+]": 350,
+      "[Sr]": 351,
+      "[Tl+3]": 352,
+      "[Sm+2]": 353,
+      "[PH5]": 354,
+      "%16": 355,
+      "[N@@+]": 356,
+      "[Au+3]": 357,
+      "[C-4]": 358,
+      "[Nd]": 359,
+      "[Ti+]": 360,
+      "[IH]": 361,
+      "[N@+]": 362,
+      "[125I]": 363,
+      "[Eu]": 364,
+      "[Sn+3]": 365,
+      "[Nb]": 366,
+      "[Er+3]": 367,
+      "[123I-]": 368,
+      "[14c]": 369,
+      "%17": 370,
+      "[SnH2]": 371,
+      "[YH]": 372,
+      "[Sb+5]": 373,
+      "[Pr+3]": 374,
+      "[Ir+]": 375,
+      "[N+3]": 376,
+      "[AlH2]": 377,
+      "[19F]": 378,
+      "%18": 379,
+      "[Tb]": 380,
+      "[14CH]": 381,
+      "[Mo+4]": 382,
+      "[Si+]": 383,
+      "[BH]": 384,
+      "[Be]": 385,
+      "[Rb]": 386,
+      "[pH]": 387,
+      "%19": 388,
+      "%20": 389,
+      "[Xe]": 390,
+      "[Ir-]": 391,
+      "[Be+2]": 392,
+      "[C+4]": 393,
+      "[RuH2]": 394,
+      "[15NH]": 395,
+      "[U+2]": 396,
+      "[Au-]": 397,
+      "%21": 398,
+      "%22": 399,
+      "[Au+]": 400,
+      "[15n]": 401,
+      "[Al+2]": 402,
+      "[Tb+3]": 403,
+      "[15N]": 404,
+      "[V+3]": 405,
+      "[W+6]": 406,
+      "[14CH3]": 407,
+      "[Cr+4]": 408,
+      "[ClH+]": 409,
+      "b": 410,
+      "[Ti+6]": 411,
+      "[Nd+]": 412,
+      "[Zr+]": 413,
+      "[PH2+]": 414,
+      "[Fm]": 415,
+      "[N@H+]": 416,
+      "[RuH]": 417,
+      "[Dy+3]": 418,
+      "%23": 419,
+      "[Hf+3]": 420,
+      "[W+4]": 421,
+      "[11C]": 422,
+      "[13CH]": 423,
+      "[Er]": 424,
+      "[124I]": 425,
+      "[LaH]": 426,
+      "[F]": 427,
+      "[siH]": 428,
+      "[Ga+]": 429,
+      "[Cm]": 430,
+      "[GeH3]": 431,
+      "[IH-]": 432,
+      "[U+6]": 433,
+      "[SeH+]": 434,
+      "[32P]": 435,
+      "[SeH-]": 436,
+      "[Pt-]": 437,
+      "[Ir+2]": 438,
+      "[se+]": 439,
+      "[U]": 440,
+      "[F+]": 441,
+      "[BH2]": 442,
+      "[As+]": 443,
+      "[Cf]": 444,
+      "[ClH2+]": 445,
+      "[Ni+]": 446,
+      "[TeH3]": 447,
+      "[SbH2]": 448,
+      "[Ag+3]": 449,
+      "%24": 450,
+      "[18O]": 451,
+      "[PH4]": 452,
+      "[Os+2]": 453,
+      "[Na-]": 454,
+      "[Sb+2]": 455,
+      "[V+4]": 456,
+      "[Ho+3]": 457,
+      "[68Ga]": 458,
+      "[PH-]": 459,
+      "[Bi+2]": 460,
+      "[Ce+2]": 461,
+      "[Pd+3]": 462,
+      "[99Tc]": 463,
+      "[13C@@H]": 464,
+      "[Fe+6]": 465,
+      "[c]": 466,
+      "[GeH2]": 467,
+      "[10B]": 468,
+      "[Cu+3]": 469,
+      "[Mo+2]": 470,
+      "[Cr+]": 471,
+      "[Pd+4]": 472,
+      "[Dy]": 473,
+      "[AsH]": 474,
+      "[Ba+]": 475,
+      "[SeH2]": 476,
+      "[In+]": 477,
+      "[TeH2]": 478,
+      "[BrH+]": 479,
+      "[14cH]": 480,
+      "[W+]": 481,
+      "[13C@H]": 482,
+      "[AsH2]": 483,
+      "[In+2]": 484,
+      "[N+2]": 485,
+      "[N@@H+]": 486,
+      "[SbH]": 487,
+      "[60Co]": 488,
+      "[AsH4+]": 489,
+      "[AsH3]": 490,
+      "[18OH]": 491,
+      "[Ru-2]": 492,
+      "[Na-2]": 493,
+      "[CuH2]": 494,
+      "[31P]": 495,
+      "[Ti+5]": 496,
+      "[35S]": 497,
+      "[P@@H]": 498,
+      "[ArH]": 499,
+      "[Co+]": 500,
+      "[Zr-2]": 501,
+      "[BH2-]": 502,
+      "[131I]": 503,
+      "[SH5]": 504,
+      "[VH]": 505,
+      "[B+2]": 506,
+      "[Yb+2]": 507,
+      "[14C@H]": 508,
+      "[211At]": 509,
+      "[NH3+2]": 510,
+      "[IrH]": 511,
+      "[IrH2]": 512,
+      "[Rh-]": 513,
+      "[Cr-]": 514,
+      "[Sb+]": 515,
+      "[Ni+3]": 516,
+      "[TaH3]": 517,
+      "[Tl+2]": 518,
+      "[64Cu]": 519,
+      "[Tc]": 520,
+      "[Cd+]": 521,
+      "[1H]": 522,
+      "[15nH]": 523,
+      "[AlH2+]": 524,
+      "[FH+2]": 525,
+      "[BiH3]": 526,
+      "[Ru-]": 527,
+      "[Mo+6]": 528,
+      "[AsH+]": 529,
+      "[BaH2]": 530,
+      "[BaH]": 531,
+      "[Fe+4]": 532,
+      "[229Th]": 533,
+      "[Th+4]": 534,
+      "[As+3]": 535,
+      "[NH+3]": 536,
+      "[P@H]": 537,
+      "[Li-]": 538,
+      "[7NaH]": 539,
+      "[Bi+]": 540,
+      "[PtH+2]": 541,
+      "[p-]": 542,
+      "[Re+5]": 543,
+      "[NiH]": 544,
+      "[Ni-]": 545,
+      "[Xe+]": 546,
+      "[Ca+]": 547,
+      "[11c]": 548,
+      "[Rh+4]": 549,
+      "[AcH]": 550,
+      "[HeH]": 551,
+      "[Sc+2]": 552,
+      "[Mn+]": 553,
+      "[UH]": 554,
+      "[14CH2]": 555,
+      "[SiH4+]": 556,
+      "[18OH2]": 557,
+      "[Ac-]": 558,
+      "[Re+4]": 559,
+      "[118Sn]": 560,
+      "[153Sm]": 561,
+      "[P+2]": 562,
+      "[9CH]": 563,
+      "[9CH3]": 564,
+      "[Y-]": 565,
+      "[NiH2]": 566,
+      "[Si+2]": 567,
+      "[Mn+6]": 568,
+      "[ZrH2]": 569,
+      "[C-2]": 570,
+      "[Bi+5]": 571,
+      "[24NaH]": 572,
+      "[Fr]": 573,
+      "[15CH]": 574,
+      "[Se+]": 575,
+      "[At]": 576,
+      "[P-3]": 577,
+      "[124I-]": 578,
+      "[CuH2-]": 579,
+      "[Nb+4]": 580,
+      "[Nb+3]": 581,
+      "[MgH]": 582,
+      "[Ir+4]": 583,
+      "[67Ga+3]": 584,
+      "[67Ga]": 585,
+      "[13N]": 586,
+      "[15OH2]": 587,
+      "[2NH]": 588,
+      "[Ho]": 589,
+      "[Cn]": 590
+    },
+    "merges": []
+  }
+}

tokenizer_config.json

@@ -0,0 +1,76 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "11": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "12": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "13": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "14": {
+      "content": "[MASK]",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "591": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "592": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "full_tokenizer_file": null,
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "[UNK]"
+}

vocab.json

@@ -0,0 +1 @@
+{"[PAD]":0,"[unused1]":1,"[unused2]":2,"[unused3]":3,"[unused4]":4,"[unused5]":5,"[unused6]":6,"[unused7]":7,"[unused8]":8,"[unused9]":9,"[unused10]":10,"[UNK]":11,"[CLS]":12,"[SEP]":13,"[MASK]":14,"c":15,"C":16,"(":17,")":18,"O":19,"1":20,"2":21,"=":22,"N":23,".":24,"n":25,"3":26,"F":27,"Cl":28,">>":29,"~":30,"-":31,"4":32,"[C@H]":33,"S":34,"[C@@H]":35,"[O-]":36,"Br":37,"#":38,"/":39,"[nH]":40,"[N+]":41,"s":42,"5":43,"o":44,"P":45,"[Na+]":46,"[Si]":47,"I":48,"[Na]":49,"[Pd]":50,"[K+]":51,"[K]":52,"[P]":53,"B":54,"[C@]":55,"[C@@]":56,"[Cl-]":57,"6":58,"[OH-]":59,"\\":60,"[N-]":61,"[Li]":62,"[H]":63,"[2H]":64,"[NH4+]":65,"[c-]":66,"[P-]":67,"[Cs+]":68,"[Li+]":69,"[Cs]":70,"[NaH]":71,"[H-]":72,"[O+]":73,"[BH4-]":74,"[Cu]":75,"7":76,"[Mg]":77,"[Fe+2]":78,"[n+]":79,"[Sn]":80,"[BH-]":81,"[Pd+2]":82,"[CH]":83,"[I-]":84,"[Br-]":85,"[C-]":86,"[Zn]":87,"[B-]":88,"[F-]":89,"[Al]":90,"[P+]":91,"[BH3-]":92,"[Fe]":93,"[C]":94,"[AlH4]":95,"[Ni]":96,"[SiH]":97,"8":98,"[Cu+2]":99,"[Mn]":100,"[AlH]":101,"[nH+]":102,"[AlH4-]":103,"[O-2]":104,"[Cr]":105,"[Mg+2]":106,"[NH3+]":107,"[S@]":108,"[Pt]":109,"[Al+3]":110,"[S@@]":111,"[S-]":112,"[Ti]":113,"[Zn+2]":114,"[PH]":115,"[NH2+]":116,"[Ru]":117,"[Ag+]":118,"[S+]":119,"[I+3]":120,"[NH+]":121,"[Ca+2]":122,"[Ag]":123,"9":124,"[Os]":125,"[Se]":126,"[SiH2]":127,"[Ca]":128,"[Ti+4]":129,"[Ac]":130,"[Cu+]":131,"[S]":132,"[Rh]":133,"[Cl+3]":134,"[cH-]":135,"[Zn+]":136,"[O]":137,"[Cl+]":138,"[SH]":139,"[H+]":140,"[Pd+]":141,"[se]":142,"[PH+]":143,"[I]":144,"[Pt+2]":145,"[C+]":146,"[Mg+]":147,"[Hg]":148,"[W]":149,"[SnH]":150,"[SiH3]":151,"[Fe+3]":152,"[NH]":153,"[Mo]":154,"[CH2+]":155,"%10":156,"[CH2-]":157,"[CH2]":158,"[n-]":159,"[Ce+4]":160,"[NH-]":161,"[Co]":162,"[I+]":163,"[PH2]":164,"[Pt+4]":165,"[Ce]":166,"[B]":167,"[Sn+2]":168,"[Ba+2]":169,"%11":170,"[Fe-3]":171,"[18F]":172,"[SH-]":173,"[Pb+2]":174,"[Os-2]":175,"[Zr+4]":176,"[N]":177,"[Ir]":178,"[Bi]":179,"[Ni+2]":180,"[P@]":181,"[Co+2]":182,"[s+]":183,"[As]":184,"[P+3]":185,"[Hg+2]":186,"[Yb+3]":187,"[CH-]":188,"[Zr+2]":189,"[Mn+2]":190,"[CH+]":191,"[In]":192,"[KH]":193,"[Ce+3]":194,"[Zr]":195,"[AlH2-]":196,"[OH2+]":197,"[Ti+3]":198,"[Rh+2]":199,"[Sb]":200,"[S-2]":201,"%12":202,"[P@@]":203,"[Si@H]":204,"[Mn+4]":205,"p":206,"[Ba]":207,"[NH2-]":208,"[Ge]":209,"[Pb+4]":210,"[Cr+3]":211,"[Au]":212,"[LiH]":213,"[Sc+3]":214,"[o+]":215,"[Rh-3]":216,"%13":217,"[Br]":218,"[Sb-]":219,"[S@+]":220,"[I+2]":221,"[Ar]":222,"[V]":223,"[Cu-]":224,"[Al-]":225,"[Te]":226,"[13c]":227,"[13C]":228,"[Cl]":229,"[PH4+]":230,"[SiH4]":231,"[te]":232,"[CH3-]":233,"[S@@+]":234,"[Rh+3]":235,"[SH+]":236,"[Bi+3]":237,"[Br+2]":238,"[La]":239,"[La+3]":240,"[Pt-2]":241,"[N@@]":242,"[PH3+]":243,"[N@]":244,"[Si+4]":245,"[Sr+2]":246,"[Al+]":247,"[Pb]":248,"[SeH]":249,"[Si-]":250,"[V+5]":251,"[Y+3]":252,"[Re]":253,"[Ru+]":254,"[Sm]":255,"*":256,"[3H]":257,"[NH2]":258,"[Ag-]":259,"[13CH3]":260,"[OH+]":261,"[Ru+3]":262,"[OH]":263,"[Gd+3]":264,"[13CH2]":265,"[In+3]":266,"[Si@@]":267,"[Si@]":268,"[Ti+2]":269,"[Sn+]":270,"[Cl+2]":271,"[AlH-]":272,"[Pd-2]":273,"[SnH3]":274,"[B+3]":275,"[Cu-2]":276,"[Nd+3]":277,"[Pb+3]":278,"[13cH]":279,"[Fe-4]":280,"[Ga]":281,"[Sn+4]":282,"[Hg+]":283,"[11CH3]":284,"[Hf]":285,"[Pr]":286,"[Y]":287,"[S+2]":288,"[Cd]":289,"[Cr+6]":290,"[Zr+3]":291,"[Rh+]":292,"[CH3]":293,"[N-3]":294,"[Hf+2]":295,"[Th]":296,"[Sb+3]":297,"%14":298,"[Cr+2]":299,"[Ru+2]":300,"[Hf+4]":301,"[14C]":302,"[Ta]":303,"[Tl+]":304,"[B+]":305,"[Os+4]":306,"[PdH2]":307,"[Pd-]":308,"[Cd+2]":309,"[Co+3]":310,"[S+4]":311,"[Nb+5]":312,"[123I]":313,"[c+]":314,"[Rb+]":315,"[V+2]":316,"[CH3+]":317,"[Ag+2]":318,"[cH+]":319,"[Mn+3]":320,"[Se-]":321,"[As-]":322,"[Eu+3]":323,"[SH2]":324,"[Sm+3]":325,"[IH+]":326,"%15":327,"[OH3+]":328,"[PH3]":329,"[IH2+]":330,"[SH2+]":331,"[Ir+3]":332,"[AlH3]":333,"[Sc]":334,"[Yb]":335,"[15NH2]":336,"[Lu]":337,"[sH+]":338,"[Gd]":339,"[18F-]":340,"[SH3+]":341,"[SnH4]":342,"[TeH]":343,"[Si@@H]":344,"[Ga+3]":345,"[CaH2]":346,"[Tl]":347,"[Ta+5]":348,"[GeH]":349,"[Br+]":350,"[Sr]":351,"[Tl+3]":352,"[Sm+2]":353,"[PH5]":354,"%16":355,"[N@@+]":356,"[Au+3]":357,"[C-4]":358,"[Nd]":359,"[Ti+]":360,"[IH]":361,"[N@+]":362,"[125I]":363,"[Eu]":364,"[Sn+3]":365,"[Nb]":366,"[Er+3]":367,"[123I-]":368,"[14c]":369,"%17":370,"[SnH2]":371,"[YH]":372,"[Sb+5]":373,"[Pr+3]":374,"[Ir+]":375,"[N+3]":376,"[AlH2]":377,"[19F]":378,"%18":379,"[Tb]":380,"[14CH]":381,"[Mo+4]":382,"[Si+]":383,"[BH]":384,"[Be]":385,"[Rb]":386,"[pH]":387,"%19":388,"%20":389,"[Xe]":390,"[Ir-]":391,"[Be+2]":392,"[C+4]":393,"[RuH2]":394,"[15NH]":395,"[U+2]":396,"[Au-]":397,"%21":398,"%22":399,"[Au+]":400,"[15n]":401,"[Al+2]":402,"[Tb+3]":403,"[15N]":404,"[V+3]":405,"[W+6]":406,"[14CH3]":407,"[Cr+4]":408,"[ClH+]":409,"b":410,"[Ti+6]":411,"[Nd+]":412,"[Zr+]":413,"[PH2+]":414,"[Fm]":415,"[N@H+]":416,"[RuH]":417,"[Dy+3]":418,"%23":419,"[Hf+3]":420,"[W+4]":421,"[11C]":422,"[13CH]":423,"[Er]":424,"[124I]":425,"[LaH]":426,"[F]":427,"[siH]":428,"[Ga+]":429,"[Cm]":430,"[GeH3]":431,"[IH-]":432,"[U+6]":433,"[SeH+]":434,"[32P]":435,"[SeH-]":436,"[Pt-]":437,"[Ir+2]":438,"[se+]":439,"[U]":440,"[F+]":441,"[BH2]":442,"[As+]":443,"[Cf]":444,"[ClH2+]":445,"[Ni+]":446,"[TeH3]":447,"[SbH2]":448,"[Ag+3]":449,"%24":450,"[18O]":451,"[PH4]":452,"[Os+2]":453,"[Na-]":454,"[Sb+2]":455,"[V+4]":456,"[Ho+3]":457,"[68Ga]":458,"[PH-]":459,"[Bi+2]":460,"[Ce+2]":461,"[Pd+3]":462,"[99Tc]":463,"[13C@@H]":464,"[Fe+6]":465,"[c]":466,"[GeH2]":467,"[10B]":468,"[Cu+3]":469,"[Mo+2]":470,"[Cr+]":471,"[Pd+4]":472,"[Dy]":473,"[AsH]":474,"[Ba+]":475,"[SeH2]":476,"[In+]":477,"[TeH2]":478,"[BrH+]":479,"[14cH]":480,"[W+]":481,"[13C@H]":482,"[AsH2]":483,"[In+2]":484,"[N+2]":485,"[N@@H+]":486,"[SbH]":487,"[60Co]":488,"[AsH4+]":489,"[AsH3]":490,"[18OH]":491,"[Ru-2]":492,"[Na-2]":493,"[CuH2]":494,"[31P]":495,"[Ti+5]":496,"[35S]":497,"[P@@H]":498,"[ArH]":499,"[Co+]":500,"[Zr-2]":501,"[BH2-]":502,"[131I]":503,"[SH5]":504,"[VH]":505,"[B+2]":506,"[Yb+2]":507,"[14C@H]":508,"[211At]":509,"[NH3+2]":510,"[IrH]":511,"[IrH2]":512,"[Rh-]":513,"[Cr-]":514,"[Sb+]":515,"[Ni+3]":516,"[TaH3]":517,"[Tl+2]":518,"[64Cu]":519,"[Tc]":520,"[Cd+]":521,"[1H]":522,"[15nH]":523,"[AlH2+]":524,"[FH+2]":525,"[BiH3]":526,"[Ru-]":527,"[Mo+6]":528,"[AsH+]":529,"[BaH2]":530,"[BaH]":531,"[Fe+4]":532,"[229Th]":533,"[Th+4]":534,"[As+3]":535,"[NH+3]":536,"[P@H]":537,"[Li-]":538,"[7NaH]":539,"[Bi+]":540,"[PtH+2]":541,"[p-]":542,"[Re+5]":543,"[NiH]":544,"[Ni-]":545,"[Xe+]":546,"[Ca+]":547,"[11c]":548,"[Rh+4]":549,"[AcH]":550,"[HeH]":551,"[Sc+2]":552,"[Mn+]":553,"[UH]":554,"[14CH2]":555,"[SiH4+]":556,"[18OH2]":557,"[Ac-]":558,"[Re+4]":559,"[118Sn]":560,"[153Sm]":561,"[P+2]":562,"[9CH]":563,"[9CH3]":564,"[Y-]":565,"[NiH2]":566,"[Si+2]":567,"[Mn+6]":568,"[ZrH2]":569,"[C-2]":570,"[Bi+5]":571,"[24NaH]":572,"[Fr]":573,"[15CH]":574,"[Se+]":575,"[At]":576,"[P-3]":577,"[124I-]":578,"[CuH2-]":579,"[Nb+4]":580,"[Nb+3]":581,"[MgH]":582,"[Ir+4]":583,"[67Ga+3]":584,"[67Ga]":585,"[13N]":586,"[15OH2]":587,"[2NH]":588,"[Ho]":589,"[Cn]":590}