Training run v20250727_153045 - F1: 88.4728, EM: 80.4825

README.md

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+---
+language: en
+tags:
+- question-answering
+- squad
+- transformers
+datasets:
+- squad
+metrics:
+- exact_match
+- f1
+model-index:
+- name: HariomSahu/albert-squad-qa
+  results:
+  - task:
+      type: question-answering
+      name: Question Answering
+    dataset:
+      name: SQuAD
+      type: squad
+    metrics:
+    - type: exact_match
+      value: N/A
+    - type: f1
+      value: 90.16042070890077
+---
+
+# albert-base-v2 fine-tuned on SQuAD
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the SQuAD dataset.
+
+## Training Details
+
+### Training Hyperparameters
+
+- **Model**: albert-base-v2
+- **Dataset**: SQuAD
+- **Optimizer**: adamw
+- **Learning Rate Scheduler**: cosine_with_restarts
+- **Learning Rate**: 1e-05
+- **Batch Size**: 20 per device
+- **Total Batch Size**: 160
+- **Epochs**: 10 (with early stopping)
+- **Weight Decay**: 0.005
+- **Warmup Ratio**: 0.03
+- **Max Gradient Norm**: 0.5
+
+### Early Stopping
+
+- **Patience**: 10
+- **Metric**: f1
+- **Best Epoch**: 2
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForQuestionAnswering
+
+tokenizer = AutoTokenizer.from_pretrained("HariomSahu/albert-squad-qa")
+model = AutoModelForQuestionAnswering.from_pretrained("HariomSahu/albert-squad-qa")
+
+# Example usage
+question = "What is the capital of France?"
+context = "France is a country in Europe. Its capital city is Paris."
+
+inputs = tokenizer(question, context, return_tensors="pt")
+outputs = model(**inputs)
+
+# Get answer
+start_scores, end_scores = outputs.start_logits, outputs.end_logits
+start_index = start_scores.argmax()
+end_index = end_scores.argmax()
+answer = tokenizer.decode(inputs["input_ids"][0][start_index:end_index+1])
+print(f"Answer: {answer}")
+```
+
+## Evaluation Results
+
+The model achieved the following results on the evaluation set:
+
+- **Exact Match**: 80.4825
+- **F1 Score**: 88.4728
+
+## Training Configuration Hash
+
+Config Hash: 5627841c
+
+This hash can be used to reproduce the exact training configuration.

config.json

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+{
+  "architectures": [
+    "AlbertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 12,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 12,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.54.0",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

eval_results.json

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+{
+  "exact_match": 83.02743614001892,
+  "f1": 90.16042070890077
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a865323a0aae82688859f4b390249e5e0fc39a95017d434f76d4c89b6f0dc413
+size 44381360

special_tokens_map.json

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+{
+  "bos_token": "[CLS]",
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "[SEP]",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[MASK]",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "eos_token": "[SEP]",
+  "extra_special_tokens": {},
+  "keep_accents": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "remove_space": true,
+  "sep_token": "[SEP]",
+  "tokenizer_class": "AlbertTokenizer",
+  "unk_token": "<unk>"
+}

training_config.json

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+{
+  "squad_v2": false,
+  "model_checkpoint": "albert-base-v2",
+  "max_length": 512,
+  "doc_stride": 64,
+  "n_best_size": 100,
+  "max_answer_length": 64,
+  "use_data_augmentation": true,
+  "augment_probability": 0.15,
+  "context_dropout": 0.05,
+  "question_paraphrasing": true,
+  "negative_sampling": true,
+  "batch_size": 20,
+  "num_epochs": 10,
+  "learning_rate": 1e-05,
+  "weight_decay": 0.005,
+  "warmup_ratio": 0.03,
+  "gradient_accumulation_steps": 2,
+  "max_grad_norm": 0.5,
+  "optimizer_type": "adamw",
+  "optimizer_betas": [
+    0.9,
+    0.98
+  ],
+  "optimizer_eps": 1e-07,
+  "scheduler_type": "cosine_with_restarts",
+  "scheduler_power": 0.5,
+  "scheduler_eta_min": 5e-07,
+  "scheduler_num_cycles": 0.5,
+  "early_stopping_patience": 10,
+  "early_stopping_threshold": 0.0002,
+  "early_stopping_metric": "f1",
+  "log_interval": 50,
+  "eval_steps": null,
+  "save_steps": null,
+  "save_total_limit": 3,
+  "wandb_project": "question-answering-enhanced",
+  "wandb_entity": null,
+  "use_wandb": true,
+  "wandb_tags": [
+    "question-answering",
+    "squad",
+    "multi-gpu"
+  ],
+  "push_to_hub": true,
+  "hub_model_id": "HariomSahu/albert-squad-qa",
+  "hub_private": false,
+  "hub_model_name_max_length": 50,
+  "hub_versioning_strategy": "single_repo_versions",
+  "hub_base_model_name": "albert-squad-qa",
+  "use_label_smoothing": true,
+  "label_smoothing_factor": 0.1,
+  "use_focal_loss": false,
+  "focal_loss_alpha": 0.25,
+  "focal_loss_gamma": 2.0,
+  "use_curriculum_learning": true,
+  "curriculum_strategy": "length_based",
+  "dropout_rate": 0.1,
+  "attention_dropout": 0.1,
+  "use_mixup": false,
+  "mixup_alpha": 0.2,
+  "seed": 42,
+  "dataloader_num_workers": 0,
+  "dataloader_pin_memory": true
+}