| --- |
| base_model: mascIT/bert-tiny-ita |
| library_name: transformers |
| metrics: |
| - accuracy |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: test_trainer |
| 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. --> |
|
|
| # test_trainer |
| |
| This model is a fine-tuned version of [mascIT/bert-tiny-ita](https://huggingface.co/mascIT/bert-tiny-ita) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5112 |
| - Accuracy: 0.9083 |
| |
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 32 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 60 | 2.0721 | 0.425 | |
| | No log | 2.0 | 120 | 1.9418 | 0.4667 | |
| | No log | 3.0 | 180 | 1.8074 | 0.5833 | |
| | No log | 4.0 | 240 | 1.6822 | 0.6333 | |
| | No log | 5.0 | 300 | 1.5631 | 0.7 | |
| | No log | 6.0 | 360 | 1.4501 | 0.7333 | |
| | No log | 7.0 | 420 | 1.3494 | 0.7583 | |
| | No log | 8.0 | 480 | 1.2584 | 0.8167 | |
| | 1.6858 | 9.0 | 540 | 1.1861 | 0.8 | |
| | 1.6858 | 10.0 | 600 | 1.1065 | 0.825 | |
| | 1.6858 | 11.0 | 660 | 1.0426 | 0.8333 | |
| | 1.6858 | 12.0 | 720 | 0.9774 | 0.8333 | |
| | 1.6858 | 13.0 | 780 | 0.9263 | 0.825 | |
| | 1.6858 | 14.0 | 840 | 0.8681 | 0.8417 | |
| | 1.6858 | 15.0 | 900 | 0.8267 | 0.85 | |
| | 1.6858 | 16.0 | 960 | 0.7704 | 0.8583 | |
| | 0.8889 | 17.0 | 1020 | 0.7324 | 0.875 | |
| | 0.8889 | 18.0 | 1080 | 0.7094 | 0.8583 | |
| | 0.8889 | 19.0 | 1140 | 0.6825 | 0.8583 | |
| | 0.8889 | 20.0 | 1200 | 0.6484 | 0.8833 | |
| | 0.8889 | 21.0 | 1260 | 0.6230 | 0.8833 | |
| | 0.8889 | 22.0 | 1320 | 0.6056 | 0.875 | |
| | 0.8889 | 23.0 | 1380 | 0.5884 | 0.8833 | |
| | 0.8889 | 24.0 | 1440 | 0.5629 | 0.9 | |
| | 0.5022 | 25.0 | 1500 | 0.5537 | 0.8917 | |
| | 0.5022 | 26.0 | 1560 | 0.5485 | 0.8917 | |
| | 0.5022 | 27.0 | 1620 | 0.5411 | 0.8833 | |
| | 0.5022 | 28.0 | 1680 | 0.5254 | 0.9083 | |
| | 0.5022 | 29.0 | 1740 | 0.5198 | 0.9083 | |
| | 0.5022 | 30.0 | 1800 | 0.5157 | 0.9083 | |
| | 0.5022 | 31.0 | 1860 | 0.5107 | 0.9083 | |
| | 0.5022 | 32.0 | 1920 | 0.5112 | 0.9083 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.0 |
| - Pytorch 2.3.1.post300 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
