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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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  model-index:
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- - name: whisper-small-ga2en-v5.1
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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-small-ga2en-v5.1
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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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  ## Model description
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@@ -42,6 +73,32 @@ The following hyperparameters were used during training:
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  - training_steps: 2000
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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  - Transformers 4.40.0
 
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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: 30.93
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+ - name: Wer
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+ type: wer
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+ value: 63.12471859522738
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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: 1.2119
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+ - Bleu: 30.93
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+ - Chrf: 49.09
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+ - Wer: 63.1247
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  ## Model description
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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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+
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+ | Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:-----:|:-----:|:---------------:|:--------:|
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+ | 2.7017 | 0.02 | 100 | 2.83 | 14.96 | 2.4392 | 169.5182 |
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+ | 2.6732 | 0.04 | 200 | 7.27 | 22.72 | 1.9552 | 103.2868 |
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+ | 2.1622 | 0.07 | 300 | 11.43 | 30.01 | 1.7297 | 108.2395 |
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+ | 2.0314 | 0.09 | 400 | 12.96 | 31.0 | 1.6499 | 106.4385 |
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+ | 1.7219 | 0.11 | 500 | 12.94 | 33.67 | 1.5543 | 107.6092 |
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+ | 1.577 | 0.13 | 600 | 12.84 | 35.03 | 1.4812 | 118.5502 |
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+ | 1.3569 | 0.1532 | 700 | 1.4559| 19.94 | 38.08 | 84.2864 |
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+ | 1.3401 | 0.1751 | 800 | 1.3855| 13.39 | 36.11 | 126.4295 |
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+ | 1.2272 | 0.1970 | 900 | 1.3764| 24.39 | 41.75 | 70.7789 |
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+ | 1.2793 | 0.2189 | 1000 | 1.3389| 23.01 | 42.13 | 80.6844 |
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+ | 1.0383 | 0.2408 | 1100 | 1.3125| 23.42 | 43.59 | 82.3953 |
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+ | 1.0485 | 0.2627 | 1200 | 1.2996| 25.42 | 42.99 | 69.4732 |
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+ | 1.0427 | 0.2846 | 1300 | 1.2996| 29.24 | 45.36 | 65.6461 |
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+ | 0.8174 | 0.3065 | 1400 | 1.2522| 27.28 | 45.67 | 68.3926 |
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+ | 0.7345 | 0.3284 | 1500 | 1.2349| 26.35 | 46.78 | 79.1986 |
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+ | 0.7551 | 0.3503 | 1600 | 1.2317| 27.81 | 46.49 | 70.6439 |
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+ | 0.6765 | 0.3722 | 1700 | 1.2062| 27.62 | 47.46 | 70.9140 |
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+ | 0.6613 | 0.3940 | 1800 | 1.2087| 26.56 | 47.12 | 72.8050 |
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+ | 0.6181 | 0.4159 | 1900 | 1.2139| 29.91 | 48.76 | 65.2859 |
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+ | 0.5809 | 0.4378 | 2000 | 1.2119| 30.93 | 49.09 | 63.1247 |
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+
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+
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  ### Framework versions
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  - Transformers 4.40.0