| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: mt5-small-task3-dataset3 |
| | 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-task3-dataset3 |
| |
|
| | 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: 1.4565 |
| | - Accuracy: 0.124 |
| | - Mse: 2.0170 |
| | - Log-distance: 0.7037 |
| | - S Score: 0.4680 |
| |
|
| | ## 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 | Mse | Log-distance | S Score | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:| |
| | | 3.3423 | 1.0 | 250 | 1.5914 | 0.074 | 2.3687 | 0.6693 | 0.4992 | |
| | | 2.3267 | 2.0 | 500 | 1.6213 | 0.102 | 2.6627 | 0.7153 | 0.4836 | |
| | | 1.8968 | 3.0 | 750 | 1.4707 | 0.118 | 2.0674 | 0.7576 | 0.4228 | |
| | | 1.7414 | 4.0 | 1000 | 1.4367 | 0.124 | 2.0643 | 0.7534 | 0.4236 | |
| | | 1.6639 | 5.0 | 1250 | 1.4493 | 0.12 | 2.0268 | 0.7079 | 0.4624 | |
| | | 1.6088 | 6.0 | 1500 | 1.4538 | 0.116 | 1.9955 | 0.6762 | 0.4924 | |
| | | 1.5823 | 7.0 | 1750 | 1.4565 | 0.124 | 2.0170 | 0.7037 | 0.4680 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| |
|
