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--- |
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language: |
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- ga |
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- en |
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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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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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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 Raw |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: IWSLT-2023, FLEURS, BiteSize, and SpokenWords |
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type: ymoslem/IWSLT2023-GA-EN |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 30.23 |
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- name: Wer |
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type: wer |
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value: 65.37595677622693 |
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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 Raw |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4321 |
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- Bleu: 30.23 |
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- Chrf: 48.18 |
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- Wer: 65.3760 |
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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: 16 |
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- eval_batch_size: 16 |
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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_ratio: 0.03 |
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- training_steps: 2000 |
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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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| 2.6013 | 0.0539 | 100 | 2.2401 | 3.18 | 17.57 | 139.4417 | |
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| 2.5749 | 0.1079 | 200 | 3.0398 | 0.0 | 3.87 | 100.4052 | |
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| 2.3449 | 0.1618 | 300 | 2.0560 | 7.53 | 24.09 | 121.0266 | |
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| 2.0392 | 0.2157 | 400 | 1.9721 | 10.7 | 29.63 | 109.7253 | |
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| 1.9155 | 0.2697 | 500 | 1.9402 | 16.73 | 31.59 | 81.9901 | |
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| 1.9148 | 0.3236 | 600 | 1.7868 | 11.12 | 32.9 | 117.1544 | |
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| 1.698 | 0.3776 | 700 | 1.7244 | 20.14 | 36.31 | 83.8811 | |
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| 1.7283 | 0.4315 | 800 | 1.6586 | 16.74 | 34.0 | 94.5070 | |
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| 1.5213 | 0.4854 | 900 | 1.6387 | 19.49 | 38.29 | 84.2413 | |
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| 1.3123 | 0.5394 | 1000 | 1.6292 | 22.27 | 41.45 | 80.2792 | |
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| 1.1584 | 0.5933 | 1100 | 1.5900 | 25.48 | 42.03 | 74.2008 | |
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| 1.1734 | 0.6472 | 1200 | 1.5495 | 17.77 | 40.1 | 106.9338 | |
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| 1.2271 | 0.7012 | 1300 | 1.4978 | 21.7 | 43.63 | 84.2413 | |
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| 1.0872 | 0.7551 | 1400 | 1.4690 | 25.34 | 43.98 | 74.2909 | |
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| 0.9331 | 0.8091 | 1500 | 1.4688 | 20.09 | 43.14 | 90.5448 | |
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| 0.7861 | 0.8630 | 1600 | 1.4284 | 26.49 | 46.76 | 76.4971 | |
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| 0.8392 | 0.9169 | 1700 | 1.3909 | 27.22 | 46.91 | 73.3904 | |
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| 0.7236 | 0.9709 | 1800 | 1.4349 | 26.98 | 46.01 | 74.2008 | |
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| 0.2741 | 1.0248 | 1900 | 1.4279 | 28.92 | 47.63 | 68.3476 | |
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| 0.2782 | 1.0787 | 2000 | 1.4321 | 30.23 | 48.18 | 65.3760 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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