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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: mt5-small-task3-dataset1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mt5-small-task3-dataset1 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3494 |
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- Accuracy: 0.156 |
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- Mse: 1.4726 |
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- Log-distance: 0.6559 |
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- S Score: 0.5092 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:| |
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| 12.3227 | 1.0 | 250 | 3.0911 | 0.126 | 1.6773 | 0.5862 | 0.5608 | |
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| 3.0171 | 2.0 | 500 | 1.8496 | 0.126 | 1.6805 | 0.5886 | 0.5608 | |
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| 2.1379 | 3.0 | 750 | 1.4488 | 0.126 | 1.6773 | 0.5862 | 0.5608 | |
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| 1.7896 | 4.0 | 1000 | 1.4309 | 0.126 | 1.6773 | 0.5862 | 0.5608 | |
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| 1.6843 | 5.0 | 1250 | 1.3863 | 0.136 | 1.5477 | 0.5660 | 0.5764 | |
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| 1.6196 | 6.0 | 1500 | 1.3676 | 0.142 | 1.4865 | 0.6943 | 0.4700 | |
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| 1.5812 | 7.0 | 1750 | 1.3518 | 0.14 | 1.4748 | 0.6894 | 0.4728 | |
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| 1.5336 | 8.0 | 2000 | 1.3538 | 0.148 | 1.6125 | 0.7828 | 0.4220 | |
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| 1.5106 | 9.0 | 2250 | 1.3468 | 0.172 | 1.4330 | 0.6204 | 0.5484 | |
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| 1.486 | 10.0 | 2500 | 1.3519 | 0.16 | 1.4487 | 0.6414 | 0.5268 | |
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| 1.4524 | 11.0 | 2750 | 1.3465 | 0.156 | 1.3796 | 0.5703 | 0.5720 | |
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| 1.4614 | 12.0 | 3000 | 1.3494 | 0.162 | 1.4250 | 0.6270 | 0.5316 | |
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| 1.4525 | 13.0 | 3250 | 1.3589 | 0.146 | 1.4602 | 0.6592 | 0.5068 | |
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| 1.4379 | 14.0 | 3500 | 1.3505 | 0.154 | 1.4722 | 0.6524 | 0.5128 | |
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| 1.4397 | 15.0 | 3750 | 1.3494 | 0.156 | 1.4726 | 0.6559 | 0.5092 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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