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--- |
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license: apache-2.0 |
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base_model: openai/whisper-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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- wer |
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- chrf |
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model-index: |
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- name: Whisper Small GA-EN Speech Translation |
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results: [] |
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datasets: |
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- ymoslem/IWSLT2023-GA-EN |
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- ymoslem/FLEURS-GA-EN |
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- ymoslem/BitesizeIrish-GA-EN |
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- ymoslem/SpokenWords-GA-EN-MTed |
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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 Small GA-EN Speech Translation |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on an unknown dataset. |
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The best model (this version) is at checkpoint 1400, epoch 1.51, and it achieves the following results on the evaluation set: |
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- Loss: 1.3989 |
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- Bleu: 28.53 |
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- Chrf: 44.93 |
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- Wer: 68.1675 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 1500 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:-----:|:-----:|:---------------:|:--------:| |
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| 2.2789 | 0.11 | 100 | 9.07 | 25.39 | 2.0838 | 102.2963 | |
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| 1.9858 | 0.22 | 200 | 12.68 | 29.42 | 1.7854 | 101.1706 | |
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| 1.6904 | 0.32 | 300 | 11.93 | 31.4 | 1.6522 | 148.2215 | |
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| 1.4934 | 0.43 | 400 | 16.44 | 35.2 | 1.5699 | 95.3174 | |
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| 1.371 | 0.54 | 500 | 15.89 | 34.46 | 1.5181 | 100.9455 | |
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| 1.1806 | 0.65 | 600 | 20.62 | 40.11 | 1.4475 | 91.8955 | |
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| 1.0781 | 0.76 | 700 | 18.55 | 40.22 | 1.4067 | 99.5948 | |
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| 0.9166 | 0.86 | 800 | 26.87 | 43.16 | 1.4104 | 71.3192 | |
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| 0.848 | 0.97 | 900 | 25.95 | 42.61 | 1.3556 | 75.6866 | |
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| 0.3712 | 1.08 | 1000 | 22.4 | 41.02 | 1.3936 | 87.2580 | |
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| 0.4415 | 1.19 | 1100 | 28.13 | 43.0 | 1.4157 | 68.0324 | |
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| 0.4166 | 1.29 | 1200 | 27.75 | 44.39 | 1.4206 | 71.1391 | |
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| 0.387 | 1.4 | 1300 | 28.48 | 44.44 | 1.4083 | 69.4282 | |
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| 0.3714 | 1.51 | 1400 | 28.53 | 44.93 | 1.3989 | 68.1675 | |
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| 0.3695 | 1.62 | 1500 | 26.13 | 43.65 | 1.4049 | 76.9923 | |
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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 |
