| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: mt5-small-task2-dataset4 |
| | 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-dataset4 |
| |
|
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4838 |
| | - Accuracy: 0.224 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 6.0046 | 1.0 | 250 | 1.3356 | 0.008 | |
| | | 1.8352 | 2.0 | 500 | 0.9395 | 0.082 | |
| | | 1.2215 | 3.0 | 750 | 0.7493 | 0.13 | |
| | | 0.9711 | 4.0 | 1000 | 0.6537 | 0.162 | |
| | | 0.8269 | 5.0 | 1250 | 0.5908 | 0.176 | |
| | | 0.741 | 6.0 | 1500 | 0.5548 | 0.19 | |
| | | 0.6896 | 7.0 | 1750 | 0.5377 | 0.194 | |
| | | 0.651 | 8.0 | 2000 | 0.5198 | 0.21 | |
| | | 0.627 | 9.0 | 2250 | 0.5086 | 0.224 | |
| | | 0.606 | 10.0 | 2500 | 0.5006 | 0.228 | |
| | | 0.5849 | 11.0 | 2750 | 0.4948 | 0.232 | |
| | | 0.5733 | 12.0 | 3000 | 0.4928 | 0.23 | |
| | | 0.5607 | 13.0 | 3250 | 0.4851 | 0.224 | |
| | | 0.5599 | 14.0 | 3500 | 0.4842 | 0.222 | |
| | | 0.5584 | 15.0 | 3750 | 0.4838 | 0.224 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| |
|
