| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: mt5-small-task2-dataset2 |
| | 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. --> |
| |
|
| | # mt5-small-task2-dataset2 |
| |
|
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4320 |
| | - Accuracy: 0.37 |
| |
|
| | ## 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: 5.6e-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: 15 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 7.018 | 1.0 | 250 | 1.2234 | 0.014 | |
| | | 1.6684 | 2.0 | 500 | 0.8157 | 0.124 | |
| | | 1.0289 | 3.0 | 750 | 0.6527 | 0.222 | |
| | | 0.8021 | 4.0 | 1000 | 0.5877 | 0.282 | |
| | | 0.6964 | 5.0 | 1250 | 0.5360 | 0.3 | |
| | | 0.6252 | 6.0 | 1500 | 0.5118 | 0.32 | |
| | | 0.5828 | 7.0 | 1750 | 0.4899 | 0.318 | |
| | | 0.5436 | 8.0 | 2000 | 0.4718 | 0.35 | |
| | | 0.5232 | 9.0 | 2250 | 0.4625 | 0.34 | |
| | | 0.5005 | 10.0 | 2500 | 0.4556 | 0.342 | |
| | | 0.4789 | 11.0 | 2750 | 0.4436 | 0.356 | |
| | | 0.4733 | 12.0 | 3000 | 0.4379 | 0.356 | |
| | | 0.4651 | 13.0 | 3250 | 0.4347 | 0.366 | |
| | | 0.4591 | 14.0 | 3500 | 0.4320 | 0.37 | |
| | | 0.4508 | 15.0 | 3750 | 0.4320 | 0.37 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Tokenizers 0.15.0 |
| |
|
