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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: 1.5832 |
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- Accuracy: 0.056 |
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- Mse: 6.6919 |
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- Log-distance: 0.6837 |
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- S Score: 0.4844 |
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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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| 10.6622 | 1.0 | 250 | 2.1479 | 0.032 | 7.8307 | 0.8081 | 0.4244 | |
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| 3.1421 | 2.0 | 500 | 1.8253 | 0.044 | 5.7385 | 0.6844 | 0.4892 | |
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| 2.3451 | 3.0 | 750 | 1.6174 | 0.04 | 5.5959 | 0.6980 | 0.4832 | |
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| 2.0073 | 4.0 | 1000 | 1.5994 | 0.046 | 6.2422 | 0.6708 | 0.4940 | |
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| 1.8357 | 5.0 | 1250 | 1.5867 | 0.05 | 6.2493 | 0.6727 | 0.4936 | |
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| 1.7782 | 6.0 | 1500 | 1.5800 | 0.048 | 6.0314 | 0.6621 | 0.4980 | |
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| 1.7333 | 7.0 | 1750 | 1.5733 | 0.056 | 6.8849 | 0.6908 | 0.4816 | |
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| 1.7219 | 8.0 | 2000 | 1.6012 | 0.056 | 6.7969 | 0.6872 | 0.4828 | |
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| 1.6886 | 9.0 | 2250 | 1.5849 | 0.038 | 6.1512 | 0.6683 | 0.4976 | |
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| 1.6804 | 10.0 | 2500 | 1.5832 | 0.056 | 6.6919 | 0.6837 | 0.4844 | |
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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 2.15.0 |
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- Tokenizers 0.15.0 |
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