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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: 25.68 |
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- name: Wer |
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type: wer |
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value: 71.04907699234579 |
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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: 1.1571 |
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- Bleu: 25.68 |
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- Chrf: 45.53 |
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- Wer: 71.0491 |
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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: 32 |
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- eval_batch_size: 32 |
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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_steps: 0.03 |
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- training_steps: 1000 |
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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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| 2.6685 | 0.07 | 100 | 2.0544 | 5.05 | 20.18 | 139.8919 | |
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| 2.4028 | 0.13 | 200 | 1.7367 | 12.29 | 29.72 | 95.5425 | |
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| 2.1231 | 0.2 | 300 | 1.6141 | 14.33 | 30.77 | 101.3958 | |
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| 1.9192 | 0.26 | 400 | 1.4778 | 16.86 | 35.65 | 91.0851 | |
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| 1.7129 | 0.33 | 500 | 1.3811 | 16.77 | 37.53 | 93.8766 | |
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| 1.5398 | 0.39 | 600 | 1.3427 | 18.85 | 39.0 | 90.2296 | |
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| 1.4257 | 0.46 | 700 | 1.2784 | 25.73 | 43.3 | 70.3287 | |
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| 1.3044 | 0.53 | 800 | 1.2274 | 25.43 | 44.33 | 72.3548 | |
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| 1.2626 | 0.59 | 900 | 1.1875 | 25.09 | 44.62 | 72.6249 | |
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| 1.2801 | 0.66 | 1000 | 1.1571 | 25.68 | 45.53 | 71.0491 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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