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--- |
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library_name: transformers |
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license: mit |
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base_model: VietAI/vit5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: ViNormT5 |
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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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# ViNormT5 |
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This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2324 |
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- Bleu Score: 79.5557 |
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- Precision: 100.0 |
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- Recall: 93.3333 |
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- Gen Len: 12.7969 |
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- Err: 56.9892 |
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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: 0.0001 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:| |
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| 0.4672 | 1.0 | 419 | 0.2390 | 76.7871 | 100.0 | 100.0 | 12.8292 | 49.7013 | |
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| 0.1742 | 2.0 | 838 | 0.2173 | 77.9698 | 100.0 | 93.3333 | 12.8076 | 54.0024 | |
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| 0.0814 | 3.0 | 1257 | 0.2010 | 79.204 | 100.0 | 93.3333 | 12.7754 | 56.6308 | |
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| 0.0382 | 4.0 | 1676 | 0.2324 | 79.5557 | 100.0 | 93.3333 | 12.7969 | 56.9892 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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