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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: 27.85 |
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- name: Wer |
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type: wer |
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value: 73.43538946420531 |
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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: 1.4107 |
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- Bleu: 27.85 |
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- Chrf: 46.91 |
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- Wer: 73.4354 |
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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: 0.01 |
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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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| 2.3549 | 0.1312 | 100 | 1.8335 | 7.17 | 24.71 | 135.7497 | |
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| 1.8906 | 0.2625 | 200 | 1.5173 | 15.56 | 34.19 | 91.5353 | |
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| 1.653 | 0.3937 | 300 | 1.3530 | 17.17 | 36.35 | 103.7371 | |
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| 1.4901 | 0.5249 | 400 | 1.3334 | 24.65 | 43.44 | 78.2530 | |
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| 1.3551 | 0.6562 | 500 | 1.2763 | 27.04 | 43.88 | 67.4471 | |
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| 1.2187 | 0.7874 | 600 | 1.2618 | 27.08 | 43.98 | 69.2031 | |
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| 1.0359 | 0.9186 | 700 | 1.2644 | 20.82 | 40.76 | 96.8483 | |
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| 0.5364 | 1.0499 | 800 | 1.3258 | 24.9 | 42.9 | 65.8262 | |
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| 0.4892 | 1.1811 | 900 | 1.3296 | 23.82 | 42.86 | 72.3098 | |
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| 0.4504 | 1.3123 | 1000 | 1.3001 | 25.78 | 43.72 | 75.5065 | |
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| 0.4161 | 1.4436 | 1100 | 1.2948 | 27.16 | 44.31 | 67.3120 | |
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| 0.3953 | 1.5748 | 1200 | 1.3261 | 29.14 | 44.65 | 65.5110 | |
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| 0.3509 | 1.7060 | 1300 | 1.3398 | 22.75 | 44.32 | 80.1441 | |
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| 0.2955 | 1.8373 | 1400 | 1.3077 | 26.29 | 42.89 | 74.8762 | |
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| 0.2801 | 1.9685 | 1500 | 1.3206 | 25.51 | 43.39 | 76.5871 | |
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| 0.1084 | 2.0997 | 1600 | 1.3609 | 28.01 | 45.59 | 68.1225 | |
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| 0.1003 | 2.2310 | 1700 | 1.3722 | 26.4 | 42.69 | 72.8501 | |
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| 0.1083 | 2.3622 | 1800 | 1.3776 | 3.81 | 19.2 | 396.1279 | |
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| 0.0939 | 2.4934 | 1900 | 1.3729 | 28.43 | 45.61 | 69.2031 | |
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| 0.0909 | 2.6247 | 2000 | 1.3834 | 27.12 | 43.39 | 67.4921 | |
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| 0.0772 | 2.7559 | 2100 | 1.4094 | 28.44 | 44.15 | 65.5110 | |
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| 0.0753 | 2.8871 | 2200 | 1.3825 | 30.5 | 46.21 | 64.9257 | |
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| 0.0438 | 3.0184 | 2300 | 1.4198 | 30.44 | 46.18 | 62.5844 | |
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| 0.0257 | 3.1496 | 2400 | 1.4033 | 31.03 | 46.67 | 63.6650 | |
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| 0.0252 | 3.2808 | 2500 | 1.4045 | 31.2 | 46.44 | 62.4043 | |
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| 0.0241 | 3.4121 | 2600 | 1.3971 | 32.42 | 48.21 | 61.1436 | |
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| 0.0208 | 3.5433 | 2700 | 1.4129 | 30.36 | 46.28 | 65.7362 | |
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| 0.0186 | 3.6745 | 2800 | 1.4076 | 31.14 | 47.73 | 64.4304 | |
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| 0.018 | 3.8058 | 2900 | 1.4151 | 27.67 | 45.87 | 73.5254 | |
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| 0.0193 | 3.9370 | 3000 | 1.4107 | 27.85 | 46.91 | 73.4354 | |
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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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