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--- |
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license: apache-2.0 |
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base_model: google/byt5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- cer |
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model-index: |
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- name: arabic_auto_correction_byt5 |
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results: |
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- task: |
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type: text-generation |
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metrics: |
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- name: BLEU |
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type: BLEU |
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value: 93.8 |
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library_name: transformers |
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pipeline_tag: text2text-generation |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/moataz-luminsoft-luminsoft/huggingface/runs/qzryl62b) |
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# arabic_auto_correction_byt5 |
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This model is a fine-tuned version of [google/byt5-small](https://huggingface.co/google/byt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0016 |
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- Cer: 0.01 |
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- Bleu: 0.9381 |
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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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- 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: 16 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | Bleu | |
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|:-------------:|:-----:|:-----:|:---------------:|:----:|:------:| |
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| No log | 1.0 | 1000 | 0.0049 | 0.03 | 0.7215 | |
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| 1.1488 | 2.0 | 2000 | 0.0034 | 0.02 | 0.8014 | |
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| 1.1488 | 3.0 | 3000 | 0.0026 | 0.01 | 0.8477 | |
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| 0.0041 | 4.0 | 4000 | 0.0022 | 0.01 | 0.8757 | |
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| 0.0041 | 5.0 | 5000 | 0.0019 | 0.01 | 0.8919 | |
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| 0.0026 | 6.0 | 6000 | 0.0018 | 0.01 | 0.8988 | |
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| 0.0026 | 7.0 | 7000 | 0.0017 | 0.01 | 0.9118 | |
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| 0.0018 | 8.0 | 8000 | 0.0016 | 0.01 | 0.9173 | |
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| 0.0018 | 9.0 | 9000 | 0.0016 | 0.01 | 0.9219 | |
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| 0.0013 | 10.0 | 10000 | 0.0016 | 0.01 | 0.9249 | |
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| 0.0013 | 11.0 | 11000 | 0.0016 | 0.01 | 0.9284 | |
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| 0.001 | 12.0 | 12000 | 0.0017 | 0.01 | 0.9318 | |
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| 0.001 | 13.0 | 13000 | 0.0016 | 0.01 | 0.9354 | |
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| 0.0008 | 14.0 | 14000 | 0.0016 | 0.01 | 0.9344 | |
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| 0.0008 | 15.0 | 15000 | 0.0016 | 0.01 | 0.9386 | |
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| 0.0006 | 16.0 | 16000 | 0.0016 | 0.01 | 0.9381 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
