| --- |
| library_name: transformers |
| license: agpl-3.0 |
| base_model: RonTon05/model_content_V2_test |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: MTL_Full_Finetuning_ESC |
| 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. --> |
|
|
| # MTL_Full_Finetuning_ESC |
| |
| This model is a fine-tuned version of [RonTon05/model_content_V2_test](https://huggingface.co/RonTon05/model_content_V2_test) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9743 |
| - F1 Task1: 0.9887 |
| - F1 Task2: 0.7758 |
| - Acc Task1: 0.9936 |
| - Acc Task2: 0.7610 |
| - F1: 0.8822 |
| - F1 Macro: 0.8822 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 Task1 | F1 Task2 | Acc Task1 | Acc Task2 | F1 | F1 Macro | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:---------:|:------:|:--------:| |
| | 1.6586 | 1.0 | 275 | 1.2293 | 0.9862 | 0.3051 | 0.9923 | 0.5981 | 0.6457 | 0.6457 | |
| | 1.0890 | 2.0 | 550 | 0.9964 | 0.9883 | 0.5148 | 0.9934 | 0.6764 | 0.7516 | 0.7516 | |
| | 0.8316 | 3.0 | 825 | 0.9017 | 0.9859 | 0.6731 | 0.9920 | 0.7209 | 0.8295 | 0.8295 | |
| | 0.6494 | 4.0 | 1100 | 0.8591 | 0.9902 | 0.7210 | 0.9945 | 0.7278 | 0.8556 | 0.8556 | |
| | 0.5126 | 5.0 | 1375 | 0.8163 | 0.9879 | 0.7489 | 0.9932 | 0.7557 | 0.8684 | 0.8684 | |
| | 0.4052 | 6.0 | 1650 | 0.8405 | 0.9887 | 0.7606 | 0.9936 | 0.7564 | 0.8746 | 0.8746 | |
| | 0.3173 | 7.0 | 1925 | 0.9193 | 0.9895 | 0.7541 | 0.9941 | 0.7448 | 0.8718 | 0.8718 | |
| | 0.2630 | 8.0 | 2200 | 0.9595 | 0.9887 | 0.7614 | 0.9936 | 0.7523 | 0.8750 | 0.8750 | |
| | 0.2193 | 9.0 | 2475 | 0.9379 | 0.9875 | 0.7789 | 0.9929 | 0.7644 | 0.8832 | 0.8832 | |
| | 0.1918 | 10.0 | 2750 | 0.9743 | 0.9887 | 0.7758 | 0.9936 | 0.7610 | 0.8822 | 0.8822 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.10.2 |
| - Pytorch 2.7.1+cu118 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
