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ymoslem
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whisper-small-ga2en-v3.1

Automatic Speech Recognition
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TensorBoard
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Irish
English
whisper
Generated from Trainer
Eval Results
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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-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-v3.1
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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-v3.1
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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 +73,42 @@ The following hyperparameters were used during training:
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  - training_steps: 3000
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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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+ - 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: 27.57
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+ - name: Wer
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+ type: wer
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+ value: 70.64385411976588
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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: 1.1870
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+ - Bleu: 27.57
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+ - Chrf: 46.72
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+ - Wer: 70.6439
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  ## Model description
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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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+
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+ | Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:-----:|:-----:|:---------------:|:--------:|
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+ | 2.6685 | 0.07 | 100 | 5.05 | 20.18 | 2.0544 | 139.8919 |
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+ | 2.4028 | 0.13 | 200 | 12.29 | 29.72 | 1.7367 | 95.5425 |
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+ | 2.1231 | 0.2 | 300 | 14.33 | 30.77 | 1.6141 | 101.3958 |
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+ | 1.9192 | 0.26 | 400 | 16.86 | 35.65 | 1.4778 | 91.0851 |
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+ | 1.7129 | 0.33 | 500 | 16.77 | 37.53 | 1.3811 | 93.8766 |
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+ | 1.5398 | 0.39 | 600 | 18.85 | 39.0 | 1.3427 | 90.2296 |
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+ | 1.4257 | 0.46 | 700 | 25.73 | 43.3 | 1.2784 | 70.3287 |
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+ | 1.3044 | 0.53 | 800 | 25.43 | 44.33 | 1.2274 | 72.3548 |
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+ | 1.2626 | 0.59 | 900 | 25.09 | 44.62 | 1.1875 | 72.6249 |
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+ | 1.2801 | 0.66 | 1000 | 25.68 | 45.53 | 1.1571 | 71.0491 |
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+ | 1.2876 | 0.72 | 1100 | 20.62 | 41.49 | 1.2193 | 85.8622 |
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+ | 1.2609 | 0.79 | 1200 | 29.47 | 45.04 | 1.2079 | 65.2859 |
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+ | 1.187 | 0.85 | 1300 | 24.65 | 43.73 | 1.2086 | 72.9851 |
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+ | 1.0342 | 0.92 | 1400 | 30.34 | 47.62 | 1.1766 | 64.3854 |
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+ | 1.0519 | 0.98 | 1500 | 29.39 | 47.69 | 1.1425 | 64.9707 |
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+ | 0.5473 | 1.05 | 1600 | 28.02 | 46.27 | 1.1842 | 67.6722 |
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+ | 0.4886 | 1.12 | 1700 | 26.62 | 46.37 | 1.1845 | 76.4971 |
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+ | 0.4354 | 1.18 | 1800 | 23.63 | 45.16 | 1.1621 | 86.1324 |
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+ | 0.4709 | 1.25 | 1900 | 27.86 | 47.3 | 1.1544 | 73.7506 |
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+ | 0.4802 | 1.31 | 2000 | 30.25 | 48.12 | 1.1571 | 64.9707 |
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+ | 0.4565 | 1.38 | 2100 | 1.2095| 24.75 | 44.7 | 77.4426 |
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+ | 0.4797 | 1.44 | 2200 | 1.2051| 28.46 | 46.03 | 67.1769 |
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+ | 0.423 | 1.51 | 2300 | 1.2079| 28.34 | 47.65 | 68.6177 |
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+ | 0.4254 | 1.58 | 2400 | 1.2251| 27.78 | 46.01 | 67.8523 |
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+ | 0.4493 | 1.64 | 2500 | 1.1898| 26.61 | 47.8 | 71.1391 |
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+ | 0.3614 | 1.71 | 2600 | 1.2079| 30.08 | 47.25 | 64.2954 |
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+ | 0.4052 | 1.77 | 2700 | 1.1975| 30.88 | 47.44 | 64.2053 |
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+ | 0.3541 | 1.84 | 2800 | 1.2006| 28.4 | 46.02 | 70.2837 |
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+ | 0.3736 | 1.9 | 2900 | 1.1906| 30.82 | 47.52 | 64.1153 |
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+ | 0.3326 | 1.97 | 3000 | 1.1870| 27.57 | 46.72 | 70.6439 |
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+
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  ### Framework versions
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  - Transformers 4.39.3
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