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--- |
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base_model: NlpHUST/t5-en-vi-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: t5-en-vi-small-ed-multi |
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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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# t5-en-vi-small-ed-multi |
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This model is a fine-tuned version of [NlpHUST/t5-en-vi-small](https://huggingface.co/NlpHUST/t5-en-vi-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 42.1043 |
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- F1 Micro: 0.0 |
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- Recall Micro: 0.0 |
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- Precision Micro: 0.0 |
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- F1 Macro: 0.0 |
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- Recall Macro: 0.0 |
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- Precision Macro: 0.0 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Recall Micro | Precision Micro | F1 Macro | Recall Macro | Precision Macro | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:| |
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| No log | 0.9987 | 393 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 2.0 | 787 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 2.9987 | 1180 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 4.0 | 1574 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 4.9936 | 1965 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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