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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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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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model-index: |
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- name: Whisper Medium GA-EN Speech Translation |
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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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# Whisper Medium GA-EN Speech Translation |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6073 |
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- Bleu: 0.22 |
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- Chrf: 12.93 |
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- Wer: 104.3224 |
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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: 0.0003 |
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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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- 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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| 4.698 | 0.11 | 100 | 4.6156 | 0.0 | 1.58 | 1852.0486 | |
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| 4.2397 | 0.22 | 200 | 4.0051 | 0.06 | 4.23 | 206.9338 | |
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| 3.8768 | 0.32 | 300 | 3.7864 | 0.18 | 5.21 | 97.9739 | |
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| 3.8755 | 0.43 | 400 | 3.6008 | 0.19 | 5.28 | 96.0378 | |
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| 3.529 | 0.54 | 500 | 3.5774 | 0.29 | 6.96 | 108.0144 | |
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| 3.32 | 0.65 | 600 | 3.5197 | 0.23 | 8.97 | 99.3697 | |
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| 3.3073 | 0.76 | 700 | 3.5056 | 0.49 | 9.43 | 104.0973 | |
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| 3.1893 | 0.86 | 800 | 3.5861 | 0.32 | 12.86 | 114.3629 | |
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| 3.0739 | 0.97 | 900 | 3.5003 | 0.6 | 12.1 | 101.3057 | |
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| 2.7718 | 1.08 | 1000 | 3.6073 | 0.22 | 12.93 | 104.3224 | |
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### Framework versions |
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- Transformers 4.39.3 |
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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 |
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