| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: mt5-small-task3-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-task3-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: 1.5208 |
| | - Accuracy: 0.06 |
| | - Mse: 4.0312 |
| | - Log-distance: 0.6188 |
| | - S Score: 0.5264 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:| |
| | | 10.5119 | 1.0 | 250 | 2.2161 | 0.016 | 4.4296 | 0.7765 | 0.4528 | |
| | | 3.0365 | 2.0 | 500 | 1.7090 | 0.026 | 4.5503 | 0.7910 | 0.4512 | |
| | | 2.2209 | 3.0 | 750 | 1.6007 | 0.052 | 4.7537 | 0.6721 | 0.4932 | |
| | | 1.9292 | 4.0 | 1000 | 1.5895 | 0.042 | 4.1466 | 0.6578 | 0.5020 | |
| | | 1.7982 | 5.0 | 1250 | 1.5695 | 0.052 | 4.7583 | 0.6732 | 0.4928 | |
| | | 1.7379 | 6.0 | 1500 | 1.5367 | 0.046 | 4.2149 | 0.6615 | 0.5000 | |
| | | 1.7081 | 7.0 | 1750 | 1.5376 | 0.054 | 4.1174 | 0.6606 | 0.5028 | |
| | | 1.6768 | 8.0 | 2000 | 1.5462 | 0.054 | 4.1031 | 0.6584 | 0.5032 | |
| | | 1.6515 | 9.0 | 2250 | 1.5256 | 0.052 | 4.1256 | 0.6525 | 0.5076 | |
| | | 1.6235 | 10.0 | 2500 | 1.5512 | 0.052 | 4.1063 | 0.6542 | 0.5040 | |
| | | 1.6289 | 11.0 | 2750 | 1.5346 | 0.06 | 4.1069 | 0.6390 | 0.5140 | |
| | | 1.6077 | 12.0 | 3000 | 1.5385 | 0.058 | 4.0832 | 0.6298 | 0.5200 | |
| | | 1.6014 | 13.0 | 3250 | 1.5204 | 0.058 | 3.9666 | 0.6236 | 0.5240 | |
| | | 1.5998 | 14.0 | 3500 | 1.5201 | 0.06 | 4.0911 | 0.6142 | 0.5304 | |
| | | 1.5994 | 15.0 | 3750 | 1.5208 | 0.06 | 4.0312 | 0.6188 | 0.5264 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Tokenizers 0.15.0 |
| |
|
