| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/flan-t5-base |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: anlp_t5_level_aware |
| | 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. --> |
| |
|
| | # anlp_t5_level_aware |
| | |
| | This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7416 |
| | |
| | ## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 0.8988 | 1.0 | 282 | 0.7789 | |
| | | 0.8497 | 2.0 | 564 | 0.7634 | |
| | | 0.8327 | 3.0 | 846 | 0.7582 | |
| | | 0.8172 | 4.0 | 1128 | 0.7516 | |
| | | 0.8039 | 5.0 | 1410 | 0.7466 | |
| | | 0.7871 | 6.0 | 1692 | 0.7470 | |
| | | 0.7856 | 7.0 | 1974 | 0.7436 | |
| | | 0.7734 | 8.0 | 2256 | 0.7427 | |
| | | 0.7737 | 9.0 | 2538 | 0.7416 | |
| | | 0.7693 | 10.0 | 2820 | 0.7416 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.1+cu128 |
| | - Datasets 4.4.1 |
| | - Tokenizers 0.22.2 |
| |
|
