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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: mt5-small-task3-dataset4 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mt5-small-task3-dataset4 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6024 |
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- Accuracy: 0.038 |
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- Mse: 6.4524 |
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- Log-distance: 0.6628 |
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- S Score: 0.4912 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:| |
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| 12.4369 | 1.0 | 250 | 2.2550 | 0.038 | 6.7116 | 0.6817 | 0.4748 | |
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| 3.1387 | 2.0 | 500 | 1.8576 | 0.024 | 5.8813 | 0.7455 | 0.4552 | |
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| 2.3265 | 3.0 | 750 | 1.6663 | 0.05 | 7.7168 | 0.7232 | 0.4556 | |
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| 1.9955 | 4.0 | 1000 | 1.6121 | 0.04 | 6.3175 | 0.6614 | 0.4908 | |
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| 1.8234 | 5.0 | 1250 | 1.6380 | 0.034 | 6.8099 | 0.6780 | 0.4860 | |
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| 1.7591 | 6.0 | 1500 | 1.5953 | 0.04 | 6.3175 | 0.6614 | 0.4908 | |
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| 1.7194 | 7.0 | 1750 | 1.5996 | 0.054 | 6.0821 | 0.6559 | 0.4976 | |
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| 1.6988 | 8.0 | 2000 | 1.5970 | 0.048 | 6.6575 | 0.6618 | 0.4952 | |
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| 1.6831 | 9.0 | 2250 | 1.6024 | 0.038 | 6.4524 | 0.6628 | 0.4912 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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