| --- |
| license: mit |
| base_model: prajjwal1/bert-tiny |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: INT03 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # INT03 |
|
|
| This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0169 |
| - Accuracy: 1.0 |
| - F1: 1.0 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | No log | 0.0 | 50 | 0.6888 | 0.62 | 0.5657 | |
| | No log | 0.01 | 100 | 0.6817 | 0.66 | 0.5965 | |
| | No log | 0.01 | 150 | 0.6004 | 0.86 | 0.8553 | |
| | No log | 0.02 | 200 | 0.4136 | 0.87 | 0.8651 | |
| | No log | 0.02 | 250 | 0.3550 | 0.89 | 0.8889 | |
| | No log | 0.03 | 300 | 0.3241 | 0.89 | 0.8889 | |
| | No log | 0.03 | 350 | 0.3144 | 0.89 | 0.8889 | |
| | No log | 0.04 | 400 | 0.3146 | 0.89 | 0.8889 | |
| | No log | 0.04 | 450 | 0.2985 | 0.89 | 0.8889 | |
| | 0.5219 | 0.05 | 500 | 0.2604 | 0.92 | 0.92 | |
| | 0.5219 | 0.05 | 550 | 0.2242 | 0.92 | 0.9202 | |
| | 0.5219 | 0.06 | 600 | 0.1976 | 0.92 | 0.9197 | |
| | 0.5219 | 0.06 | 650 | 0.1800 | 0.93 | 0.9302 | |
| | 0.5219 | 0.07 | 700 | 0.1685 | 0.93 | 0.9302 | |
| | 0.5219 | 0.07 | 750 | 0.1706 | 0.93 | 0.9303 | |
| | 0.5219 | 0.08 | 800 | 0.1532 | 0.93 | 0.9303 | |
| | 0.5219 | 0.08 | 850 | 0.1411 | 0.93 | 0.9303 | |
| | 0.5219 | 0.09 | 900 | 0.1070 | 0.98 | 0.9799 | |
| | 0.5219 | 0.09 | 950 | 0.0970 | 0.96 | 0.9601 | |
| | 0.2869 | 0.1 | 1000 | 0.0775 | 0.96 | 0.9601 | |
| | 0.2869 | 0.1 | 1050 | 0.0789 | 0.97 | 0.9701 | |
| | 0.2869 | 0.11 | 1100 | 0.0546 | 0.98 | 0.98 | |
| | 0.2869 | 0.11 | 1150 | 0.0789 | 0.98 | 0.9800 | |
| | 0.2869 | 0.12 | 1200 | 0.0425 | 0.99 | 0.9900 | |
| | 0.2869 | 0.12 | 1250 | 0.0443 | 0.99 | 0.9900 | |
| | 0.2869 | 0.13 | 1300 | 0.0340 | 0.99 | 0.9900 | |
| | 0.2869 | 0.13 | 1350 | 0.0649 | 0.97 | 0.9700 | |
| | 0.2869 | 0.14 | 1400 | 0.0241 | 1.0 | 1.0 | |
| | 0.2869 | 0.14 | 1450 | 0.0215 | 1.0 | 1.0 | |
| | 0.1754 | 0.15 | 1500 | 0.0146 | 1.0 | 1.0 | |
| | 0.1754 | 0.15 | 1550 | 0.0125 | 1.0 | 1.0 | |
| | 0.1754 | 0.16 | 1600 | 0.0122 | 1.0 | 1.0 | |
| | 0.1754 | 0.16 | 1650 | 0.0110 | 1.0 | 1.0 | |
| | 0.1754 | 0.17 | 1700 | 0.0092 | 1.0 | 1.0 | |
| | 0.1754 | 0.17 | 1750 | 0.0117 | 1.0 | 1.0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
|
|
