| --- |
| library_name: transformers |
| license: agpl-3.0 |
| base_model: RonTon05/model_content_V2_test |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: multi_task_model_general_fine_tune |
| 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. --> |
|
|
| # multi_task_model_general_fine_tune |
| |
| 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: |
| - Acc Content: 0.9775 |
| - F1 Content: 0.9612 |
| - Acc Classification: 0.8299 |
| - F1 Classification: 0.7954 |
| - Loss: 0.6929 |
| |
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - 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: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Acc Content | F1 Content | Acc Classification | F1 Classification | Validation Loss | |
| |:-------------:|:-----:|:----:|:-----------:|:----------:|:------------------:|:-----------------:|:---------------:| |
| | No log | 1.0 | 276 | 0.9751 | 0.9569 | 0.8056 | 0.7523 | 0.7369 | |
| | 0.5614 | 2.0 | 552 | 0.9755 | 0.9582 | 0.8161 | 0.7741 | 0.6704 | |
| | 0.5614 | 3.0 | 828 | 0.9760 | 0.9582 | 0.8201 | 0.7709 | 0.6735 | |
| | 0.3769 | 4.0 | 1104 | 0.9766 | 0.9595 | 0.8263 | 0.7853 | 0.6859 | |
| | 0.3769 | 5.0 | 1380 | 0.9775 | 0.9612 | 0.8299 | 0.7954 | 0.6929 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.57.1 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 4.4.1 |
| - Tokenizers 0.22.1 |
|
|
