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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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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- wer |
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- chrf |
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model-index: |
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- name: Whisper Tiny GA-EN Speech Translation v.1.4 |
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results: [] |
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datasets: |
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- ymoslem/IWSLT2023-GA-EN |
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language: |
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- ga |
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- en |
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library_name: transformers |
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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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# Whisper Tiny GA-EN Speech Translation v.1.4 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on an unknown dataset. |
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The best model (this version) is at checkpoint 500, epoch 7.35, and it achieves the following results on the evaluation set: |
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- Loss: 2.5784 |
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- Bleu: 17.0 |
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- Chrf: 30.42 |
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- Wer: 85.8622 |
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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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### Experiment |
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As this is a translation task into English, use `language="English"` |
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``` |
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tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-tiny", |
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cache_dir=cache_dir, |
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language="english", |
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task="translate") |
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``` |
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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: 128 |
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- eval_batch_size: 128 |
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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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- lr_scheduler_warmup_steps: 0.03 |
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- training_steps: 1000 |
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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 | Bleu | Chrf | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:| |
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| 0.8117 | 1.47 | 100 | 2.1773 | 8.81 | 24.15 | 119.9910 | |
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| 0.3555 | 2.94 | 200 | 2.2596 | 11.81 | 27.7 | 110.8510 | |
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| 0.0872 | 4.41 | 300 | 2.4108 | 12.89 | 28.57 | 110.5808 | |
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| 0.063 | 5.88 | 400 | 2.5306 | 12.67 | 27.78 | 107.1139 | |
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| 0.034 | 7.35 | 500 | 2.5784 | 17.0 | 30.42 | 85.8622 | |
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| 0.0349 | 8.82 | 600 | 2.6201 | 16.64 | 29.98 | 86.8978 | |
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| 0.0198 | 10.29 | 700 | 2.7151 | 16.0 | 30.04 | 88.2936 | |
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| 0.0134 | 11.76 | 800 | 2.7159 | 14.16 | 30.03 | 105.0878 | |
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| 0.0088 | 13.24 | 900 | 2.7369 | 14.61 | 29.32 | 94.3269 | |
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| 0.0056 | 14.71 | 1000 | 2.7420 | 14.71 | 30.02 | 95.7226 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
