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README.md CHANGED
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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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  model-index:
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- - name: whisper-medium-ga2en-v1.2
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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-ga2en-v1.2
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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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  ## Model description
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@@ -44,6 +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 4.39.3
 
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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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+ 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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+ - 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: 27.06
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+ - name: Wer
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+ type: wer
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+ value: 73.4804142278253
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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-small](https://huggingface.co/openai/whisper-small) 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: 1.2998
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+ - Bleu: 27.06
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+ - Chrf: 47.61
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+ - Wer: 73.4804
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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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+ | 2.5227 | 0.05 | 100 | 1.05 | 12.82 | 2.4253 | 343.2238 |
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+ | 2.4775 | 0.11 | 200 | 10.04 | 24.39 | 2.0665 | 95.2724 |
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+ | 2.114 | 0.16 | 300 | 8.79 | 28.6 | 1.9792 | 141.9181 |
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+ | 1.9813 | 0.22 | 400 | 17.5 | 33.84 | 1.7596 | 82.8906 |
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+ | 1.6979 | 0.27 | 500 | 13.89 | 33.51 | 1.6820 | 115.0383 |
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+ | 1.7157 | 0.32 | 600 | 18.54 | 36.44 | 1.5795 | 91.4003 |
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+ | 1.3845 | 0.38 | 700 | 19.51 | 39.03 | 1.4989 | 88.7888 |
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+ | 1.3803 | 0.43 | 800 | 25.18 | 40.96 | 1.4176 | 69.5182 |
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+ | 1.1 | 0.49 | 900 | 28.98 | 44.78 | 1.3666 | 65.9613 |
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+ | 1.1843 | 0.54 | 1000 | 27.59 | 45.91 | 1.3298 | 70.4638 |
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+ | 1.1317 | 0.59 | 1100 | 1.5018| 20.22 | 41.14 | 86.9878 |
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+ | 1.071 | 0.65 | 1200 | 1.4600| 20.67 | 40.43 | 85.6371 |
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+ | 1.1542 | 0.7 | 1300 | 1.4114| 26.84 | 43.76 | 69.5182 |
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+ | 1.0729 | 0.76 | 1400 | 1.4056| 22.98 | 42.65 | 78.0729 |
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+ | 0.8747 | 0.81 | 1500 | 1.3537| 24.65 | 44.89 | 73.4804 |
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+ | 0.8626 | 0.86 | 1600 | 1.3391| 28.0 | 46.03 | 68.7978 |
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+ | 0.7643 | 0.92 | 1700 | 1.3250| 27.23 | 45.31 | 70.3287 |
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+ | 0.6971 | 0.97 | 1800 | 1.2795| 30.05 | 48.28 | 65.5110 |
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+ | 0.3055 | 1.02 | 1900 | 1.2994| 27.41 | 47.91 | 71.1842 |
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+ | 0.2801 | 1.08 | 2000 | 1.2998| 27.06 | 47.61 | 73.4804 |
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+
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+
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  ### Framework versions
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  - Transformers 4.39.3
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