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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-medium |
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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 Raw |
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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: 26.56 |
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- name: Wer |
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type: wer |
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value: 76.67717244484467 |
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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 Raw |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) 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: 1.5187 |
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- Bleu: 26.56 |
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- Chrf: 46.91 |
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- Wer: 76.6772 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 0.03 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:-----:|:-----:|:---------------:|:--------:| |
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| 2.5874 | 0.0539 | 100 | 4.9 | 19.49 | 2.1785 | 114.0027 | |
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| 2.3237 | 0.1079 | 200 | 6.48 | 22.77 | 2.1129 | 151.8235 | |
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| 2.192 | 0.1618 | 300 | 7.92 | 25.9 | 2.0182 | 148.6718 | |
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| 1.9861 | 0.2157 | 400 | 10.55 | 28.55 | 1.8607 | 121.0266 | |
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| 1.8893 | 0.2697 | 500 | 16.68 | 33.64 | 1.8560 | 89.7794 | |
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| 1.8526 | 0.3236 | 600 | 8.83 | 30.12 | 1.7738 | 166.9968 | |
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| 1.6537 | 0.3776 | 700 | 10.94 | 33.83 | 1.6781 | 152.2287 | |
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| 1.7103 | 0.4315 | 800 | 16.9 | 36.4 | 1.6389 | 92.2557 | |
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| 1.4837 | 0.4854 | 900 | 13.81 | 34.5 | 1.6077 | 124.2233 | |
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| 1.2784 | 0.5394 | 1000 | 14.79 | 37.53 | 1.6103 | 116.3440 | |
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| 1.111 | 0.5933 | 1100 | 19.31 | 39.0 | 1.5579 | 93.6965 | |
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| 1.167 | 0.6472 | 1200 | 20.88 | 41.7 | 1.5210 | 91.6704 | |
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| 1.2217 | 0.7012 | 1300 | 21.29 | 41.72 | 1.4719 | 84.9167 | |
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| 1.0613 | 0.7551 | 1400 | 28.3 | 44.37 | 1.4663 | 67.1319 | |
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| 0.9256 | 0.8091 | 1500 | 27.5 | 45.59 | 1.4258 | 68.7078 | |
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| 0.8023 | 0.8630 | 1600 | 27.1 | 46.27 | 1.4027 | 72.7600 | |
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| 0.8327 | 0.9169 | 1700 | 27.03 | 46.19 | 1.3784 | 73.0302 | |
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| 0.7019 | 0.9709 | 1800 | 28.91 | 46.34 | 1.4127 | 67.4921 | |
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| 0.2681 | 1.0248 | 1900 | 28.53 | 47.12 | 1.3955 | 68.3026 | |
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| 0.2659 | 1.0787 | 2000 | 28.37 | 45.85 | 1.4194 | 68.1225 | |
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| 0.4202 | 1.1327 | 2100 | 1.5449| 27.53 | 44.0 | 69.8784 | |
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| 0.4212 | 1.1866 | 2200 | 1.6060| 25.89 | 43.05 | 70.1036 | |
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| 0.4124 | 1.2406 | 2300 | 1.6167| 24.31 | 41.55 | 75.8217 | |
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| 0.4696 | 1.2945 | 2400 | 1.5904| 21.79 | 41.86 | 85.0968 | |
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| 0.4018 | 1.3484 | 2500 | 1.6300| 25.36 | 43.45 | 76.4070 | |
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| 0.4549 | 1.4024 | 2600 | 1.5540| 26.06 | 44.27 | 71.9946 | |
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| 0.4018 | 1.4563 | 2700 | 1.5721| 26.22 | 45.42 | 72.9851 | |
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| 0.3534 | 1.5102 | 2800 | 1.5488| 23.65 | 44.43 | 80.0090 | |
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| 0.2907 | 1.5642 | 2900 | 1.5494| 24.04 | 42.57 | 75.3715 | |
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| 0.3117 | 1.6181 | 3000 | 1.5691| 28.27 | 45.06 | 67.2670 | |
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| 0.3379 | 1.6721 | 3100 | 1.4951| 30.52 | 47.42 | 65.5561 | |
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| 0.3686 | 1.7260 | 3200 | 1.5010| 30.7 | 48.13 | 64.8357 | |
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| 0.2855 | 1.7799 | 3300 | 1.5197| 27.19 | 46.47 | 74.5610 | |
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| 0.2919 | 1.8339 | 3400 | 1.4974| 31.39 | 48.56 | 63.5299 | |
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| 0.2582 | 1.8878 | 3500 | 1.4779| 30.18 | 48.54 | 64.9257 | |
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| 0.2523 | 1.9417 | 3600 | 1.4835| 30.29 | 47.07 | 66.6367 | |
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| 0.2005 | 1.9957 | 3700 | 1.4682| 29.89 | 47.95 | 68.2125 | |
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| 0.0617 | 2.0496 | 3800 | 1.5221| 29.49 | 47.1 | 67.6272 | |
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| 0.0661 | 2.1036 | 3900 | 1.5142| 26.93 | 46.91 | 75.8217 | |
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| 0.0609 | 2.1575 | 4000 | 1.5187| 26.56 | 46.91 | 76.6772 | |
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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 2.20.0 |
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- Tokenizers 0.19.1 |
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