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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: Vi-gec5
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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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# Vi-gec5
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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: 0.0927
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- Wer: 2.9213
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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: 5e-06
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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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- gradient_accumulation_steps: 2
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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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- lr_scheduler_warmup_steps: 500
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- training_steps: 1167
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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 | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.7673 | 0.41 | 233 | 0.6208 | 191.2360 |
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| 0.4518 | 0.81 | 466 | 0.1819 | 34.3105 |
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| 0.2424 | 1.22 | 699 | 0.1073 | 4.2510 |
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| 0.2037 | 1.63 | 932 | 0.0955 | 3.2135 |
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| 0.1995 | 2.04 | 1165 | 0.0927 | 2.9213 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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