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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-small |
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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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- ymoslem/Tatoeba-Speech-Irish |
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- ymoslem/Wikimedia-Speech-Irish |
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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 Small GA-EN Speech Translation |
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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, SpokenWords, Tatoeba, and Wikimedia |
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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: 32.04 |
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- name: Wer |
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type: wer |
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value: 63.39486717694732 |
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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 the IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4631 |
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- Bleu: 32.04 |
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- Chrf: 48.69 |
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- Wer: 63.3949 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 3000 |
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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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| 2.3783 | 0.1312 | 100 | 1.8852 | 7.56 | 22.6 | 113.2823 | |
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| 1.92 | 0.2625 | 200 | 1.5276 | 16.93 | 32.19 | 81.4498 | |
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| 1.6661 | 0.3937 | 300 | 1.3907 | 16.26 | 35.75 | 99.1896 | |
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| 1.4712 | 0.5249 | 400 | 1.3126 | 24.55 | 42.56 | 77.8478 | |
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| 1.3404 | 0.6562 | 500 | 1.2960 | 23.94 | 42.25 | 77.3976 | |
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| 1.2106 | 0.7874 | 600 | 1.2556 | 23.82 | 43.46 | 73.5705 | |
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| 1.0312 | 0.9186 | 700 | 1.3002 | 23.73 | 43.09 | 74.6060 | |
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| 0.5265 | 1.0499 | 800 | 1.2993 | 28.09 | 45.57 | 69.1580 | |
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| 0.4802 | 1.1811 | 900 | 1.3466 | 25.21 | 43.38 | 75.7767 | |
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| 0.4415 | 1.3123 | 1000 | 1.3456 | 29.77 | 47.56 | 66.9968 | |
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| 0.4164 | 1.4436 | 1100 | 1.3373 | 27.92 | 45.54 | 70.9140 | |
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| 0.3937 | 1.5748 | 1200 | 1.3162 | 30.09 | 46.51 | 64.2053 | |
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| 0.3391 | 1.7060 | 1300 | 1.3424 | 24.82 | 45.35 | 72.9401 | |
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| 0.2969 | 1.8373 | 1400 | 1.3271 | 31.78 | 48.51 | 62.5394 | |
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| 0.2755 | 1.9685 | 1500 | 1.3523 | 31.6 | 48.33 | 61.3237 | |
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| 0.1059 | 2.0997 | 1600 | 1.3910 | 30.26 | 45.88 | 65.3309 | |
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| 0.0975 | 2.2310 | 1700 | 1.4255 | 30.28 | 46.1 | 64.1603 | |
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| 0.1047 | 2.3622 | 1800 | 1.3923 | 29.99 | 46.44 | 64.9257 | |
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| 0.0874 | 2.4934 | 1900 | 1.4111 | 30.14 | 47.09 | 65.1058 | |
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| 0.0838 | 2.6247 | 2000 | 1.4378 | 25.63 | 45.79 | 77.4426 | |
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| 0.0757 | 2.7559 | 2100 | 1.4356 | 29.28 | 47.5 | 65.0608 | |
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| 0.0749 | 2.8871 | 2200 | 1.4532 | 30.56 | 46.58 | 64.3854 | |
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| 0.0463 | 3.0184 | 2300 | 1.4324 | 32.69 | 49.04 | 62.6294 | |
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| 0.0265 | 3.1496 | 2400 | 1.4311 | 31.24 | 48.58 | 62.9896 | |
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| 0.0266 | 3.2808 | 2500 | 1.4409 | 31.97 | 47.99 | 62.4944 | |
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| 0.0237 | 3.4121 | 2600 | 1.4310 | 32.44 | 48.86 | 62.2692 | |
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| 0.0208 | 3.5433 | 2700 | 1.4483 | 31.3 | 47.49 | 63.5299 | |
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| 0.0185 | 3.6745 | 2800 | 1.4513 | 32.86 | 48.98 | 62.6294 | |
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| 0.0178 | 3.8058 | 2900 | 1.4583 | 31.77 | 48.91 | 63.0797 | |
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| 0.0194 | 3.9370 | 3000 | 1.4631 | 32.04 | 48.69 | 63.3949 | |
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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 2.19.2 |
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- Tokenizers 0.19.1 |
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