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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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- 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, 1 epoch, 10k steps |
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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: 34.31 |
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- name: Wer |
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type: wer |
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value: 59.70283656010806 |
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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, 1 epoch, 10k steps |
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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, SpokenWords, Tatoeba, and Wikimedia dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3521 |
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- Bleu: 34.31 |
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- Chrf: 52.5 |
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- Wer: 59.7028 |
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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: 0.02 |
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- training_steps: 13000 |
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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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| 2.6291 | 0.0109 | 100 | 2.33 | 16.34 | 2.1971 | 175.5516 | |
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| 2.6591 | 0.0219 | 200 | 5.57 | 22.49 | 2.0357 | 122.2873 | |
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| 2.5637 | 0.0328 | 300 | 7.67 | 26.29 | 1.8690 | 133.0032 | |
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| 2.2954 | 0.0438 | 400 | 11.2 | 30.03 | 1.8062 | 114.2278 | |
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| 2.3292 | 0.0547 | 500 | 9.85 | 29.28 | 1.7421 | 117.2895 | |
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| 2.1223 | 0.0657 | 600 | 14.56 | 32.56 | 1.6739 | 84.2864 | |
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| 2.2398 | 0.0766 | 700 | 13.86 | 34.74 | 1.7187 | 98.9644 | |
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| 2.002 | 0.0876 | 800 | 15.53 | 36.64 | 1.6392 | 96.7582 | |
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| 1.8611 | 0.0985 | 900 | 15.8 | 36.32 | 1.6283 | 94.3719 | |
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| 1.8498 | 0.1095 | 1000 | 17.58 | 36.0 | 1.6102 | 85.5921 | |
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| 1.7585 | 0.1204 | 1100 | 15.91 | 36.61 | 1.6337 | 100.2251 | |
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| 1.6115 | 0.1314 | 1200 | 22.21 | 39.94 | 1.5381 | 76.8122 | |
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| 1.4415 | 0.1423 | 1300 | 20.36 | 37.87 | 1.5864 | 79.1986 | |
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| 1.5103 | 0.1533 | 1400 | 23.2 | 41.26 | 1.4925 | 75.2364 | |
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| 1.6576 | 0.1642 | 1500 | 18.12 | 40.49 | 1.4508 | 102.9266 | |
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| 1.3429 | 0.1752 | 1600 | 27.88 | 43.74 | 1.4399 | 69.7884 | |
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| 1.2522 | 0.1861 | 1700 | 23.04 | 43.31 | 1.4256 | 77.1724 | |
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| 1.2018 | 0.1970 | 1800 | 21.06 | 40.39 | 1.4072 | 78.6583 | |
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| 1.1945 | 0.2080 | 1900 | 23.0 | 42.71 | 1.4222 | 76.7222 | |
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| 1.1869 | 0.2189 | 2000 | 22.54 | 42.02 | 1.3992 | 75.8667 | |
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| 1.1752 | 0.2299 | 2100 | 20.81 | 41.07 | 1.3926 | 79.5137 | |
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| 1.0281 | 0.2408 | 2200 | 27.24 | 45.55 | 1.3633 | 69.6083 | |
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| 0.894 | 0.2518 | 2300 | 28.6 | 45.58 | 1.3287 | 65.8712 | |
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| 0.9788 | 0.2627 | 2400 | 27.75 | 46.21 | 1.3138 | 69.2931 | |
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| 0.8418 | 0.2737 | 2500 | 27.85 | 46.17 | 1.3064 | 68.3026 | |
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| 0.7559 | 0.2846 | 2600 | 28.44 | 48.52 | 1.2903 | 68.3476 | |
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| 0.8632 | 0.2956 | 2700 | 27.87 | 46.86 | 1.2834 | 68.3476 | |
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| 0.7501 | 0.3065 | 2800 | 28.63 | 49.25 | 1.2669 | 68.5277 | |
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| 0.6953 | 0.3175 | 2900 | 30.46 | 48.83 | 1.2615 | 64.4304 | |
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| 0.7195 | 0.3284 | 3000 | 27.49 | 47.94 | 1.2514 | 71.0941 | |
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| 0.6155 | 0.3394 | 3100 | 30.06 | 49.64 | 1.2428 | 66.5916 | |
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| 0.605 | 0.3503 | 3200 | 31.64 | 50.27 | 1.2040 | 63.8451 | |
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| 0.6349 | 0.3612 | 3300 | 28.96 | 49.35 | 1.2077 | 65.3760 | |
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| 0.4669 | 0.3722 | 3400 | 31.17 | 48.95 | 1.2219 | 64.2503 | |
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| 0.5196 | 0.3831 | 3500 | 30.97 | 50.13 | 1.2124 | 63.8001 | |
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| 0.5141 | 0.3941 | 3600 | 31.97 | 50.8 | 1.2026 | 63.0347 | |
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| 0.4221 | 0.4050 | 3700 | 31.76 | 51.35 | 1.1893 | 63.4399 | |
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| 0.2951 | 0.4160 | 3800 | 32.4 | 51.08 | 1.2049 | 63.1247 | |
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| 0.3898 | 0.4269 | 3900 | 32.15 | 51.09 | 1.1906 | 63.5299 | |
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| 0.4071 | 0.4379 | 4000 | 33.1 | 51.85 | 1.1873 | 62.4043 | |
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| 0.3975 | 0.4488 | 4100 | 29.58 | 49.33 | 1.2117 | 70.3287 | |
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| 0.4206 | 0.4598 | 4200 | 31.69 | 50.8 | 1.2150 | 65.0158 | |
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| 0.2935 | 0.4707 | 4300 | 32.9 | 50.01 | 1.2484 | 62.8546 | |
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| 0.3718 | 0.4817 | 4400 | 31.64 | 50.55 | 1.2055 | 63.8451 | |
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| 0.3722 | 0.4926 | 4500 | 28.16 | 49.28 | 1.2200 | 70.4638 | |
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| 0.2986 | 0.5036 | 4600 | 28.76 | 49.9 | 1.2240 | 68.7528 | |
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| 0.3327 | 0.5145 | 4700 | 29.34 | 49.67 | 1.2052 | 67.5822 | |
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| 0.2489 | 0.5255 | 4800 | 32.52 | 51.77 | 1.2083 | 62.4493 | |
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| 0.3653 | 0.5364 | 4900 | 31.48 | 51.16 | 1.2166 | 63.8451 | |
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| 0.3326 | 0.5473 | 5000 | 33.04 | 51.71 | 1.2169 | 62.4493 | |
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| 0.3045 | 0.5583 | 5100 | 27.45 | 48.22 | 1.2460 | 68.9779 | |
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| 0.3444 | 0.5692 | 5200 | 33.14 | 50.76 | 1.2829 | 62.2692 | |
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| 0.3236 | 0.5802 | 5300 | 28.89 | 49.37 | 1.2499 | 70.3737 | |
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| 0.3004 | 0.5911 | 5400 | 29.89 | 49.29 | 1.3165 | 68.7078 | |
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| 0.3019 | 0.6021 | 5500 | 32.8 | 49.78 | 1.2782 | 62.8095 | |
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| 0.2923 | 0.6130 | 5600 | 31.75 | 50.26 | 1.2468 | 63.3498 | |
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| 0.3237 | 0.6240 | 5700 | 34.4 | 52.59 | 1.2511 | 61.0986 | |
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| 0.2226 | 0.6349 | 5800 | 30.51 | 50.38 | 1.2479 | 63.3498 | |
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| 0.2207 | 0.6459 | 5900 | 32.68 | 51.97 | 1.2641 | 62.1342 | |
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| 0.2017 | 0.6568 | 6000 | 32.47 | 51.36 | 1.2640 | 62.6745 | |
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| 0.201 | 0.6678 | 6100 | 33.6 | 52.29 | 1.2774 | 61.4588 | |
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| 0.203 | 0.6787 | 6200 | 30.27 | 50.84 | 1.2670 | 65.6461 | |
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| 0.1456 | 0.6897 | 6300 | 31.2 | 51.05 | 1.2656 | 63.3048 | |
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| 0.1607 | 0.7006 | 6400 | 30.39 | 51.04 | 1.2611 | 65.8262 | |
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| 0.1933 | 0.7115 | 6500 | 31.78 | 50.92 | 1.2545 | 63.0797 | |
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| 0.1537 | 0.7225 | 6600 | 30.18 | 50.18 | 1.2500 | 64.7006 | |
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| 0.1279 | 0.7334 | 6700 | 33.23 | 51.0 | 1.2548 | 59.8379 | |
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| 0.1189 | 0.7444 | 6800 | 33.51 | 50.67 | 1.2594 | 61.1887 | |
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| 0.1056 | 0.7553 | 6900 | 32.97 | 51.02 | 1.2578 | 61.9991 | |
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| 0.1105 | 0.7663 | 7000 | 32.74 | 50.83 | 1.2569 | 62.0441 | |
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| 0.1183 | 0.7772 | 7100 | 34.07 | 52.2 | 1.2590 | 60.4232 | |
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| 0.1373 | 0.7882 | 7200 | 33.55 | 50.6 | 1.2430 | 61.2787 | |
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| 0.1325 | 0.7991 | 7300 | 32.36 | 50.39 | 1.2548 | 62.3143 | |
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| 0.0907 | 0.8101 | 7400 | 32.28 | 50.99 | 1.2578 | 61.2787 | |
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| 0.0919 | 0.8210 | 7500 | 33.01 | 51.81 | 1.2791 | 60.4683 | |
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| 0.0852 | 0.8320 | 7600 | 32.97 | 51.56 | 1.2782 | 61.5489 | |
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| 0.1223 | 0.8429 | 7700 | 33.57 | 52.33 | 1.2638 | 59.9280 | |
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| 0.0826 | 0.8539 | 7800 | 33.83 | 52.7 | 1.2634 | 60.1531 | |
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| 0.0783 | 0.8648 | 7900 | 33.79 | 52.31 | 1.2595 | 60.1081 | |
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| 0.0986 | 0.8758 | 8000 | 34.33 | 52.54 | 1.2608 | 59.4327 | |
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| 0.1148 | 0.8867 | 8100 | 34.03 | 52.52 | 1.2736 | 59.8829 | |
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| 0.1134 | 0.8976 | 8200 | 34.14 | 51.64 | 1.3073 | 61.5038 | |
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| 0.1166 | 0.9086 | 8300 | 30.51 | 49.26 | 1.3385 | 65.5561 | |
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| 0.0871 | 0.9195 | 8400 | 32.31 | 51.06 | 1.3313 | 62.5394 | |
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| 0.0927 | 0.9305 | 8500 | 28.64 | 48.43 | 1.3898 | 69.3832 | |
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| 0.1012 | 0.9414 | 8600 | 33.12 | 52.02 | 1.3144 | 61.4138 | |
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| 0.0742 | 0.9524 | 8700 | 33.68 | 51.38 | 1.3284 | 61.7740 | |
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| 0.0802 | 0.9633 | 8800 | 34.33 | 51.38 | 1.3300 | 61.4138 | |
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| 0.0799 | 0.9743 | 8900 | 33.72 | 50.77 | 1.3328 | 60.1981 | |
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| 0.0936 | 0.9852 | 9000 | 34.76 | 51.4 | 1.3181 | 60.0630 | |
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| 0.1091 | 0.9962 | 9100 | 35.13 | 52.6 | 1.3096 | 59.9730 | |
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| 0.0427 | 1.0071 | 9200 | 35.49 | 53.12 | 1.2905 | 59.8379 | |
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| 0.0338 | 1.0181 | 9300 | 35.33 | 52.62 | 1.3097 | 60.5133 | |
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| 0.0363 | 1.0290 | 9400 | 35.51 | 53.06 | 1.3172 | 59.6128 | |
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| 0.0319 | 1.0400 | 9500 | 36.82 | 53.6 | 1.3166 | 58.3971 | |
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| 0.0434 | 1.0509 | 9600 | 35.62 | 53.28 | 1.3050 | 59.6578 | |
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| 0.0218 | 1.0619 | 9700 | 35.57 | 53.28 | 1.3096 | 59.5227 | |
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| 0.0316 | 1.0728 | 9800 | 36.14 | 53.87 | 1.3162 | 58.3971 | |
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| 0.0315 | 1.0837 | 9900 | 36.26 | 54.16 | 1.3121 | 58.3521 | |
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| 0.0229 | 1.0947 | 10000 | 36.12 | 53.74 | 1.3134 | 58.3071 | |
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| 0.0561 | 1.1056 | 10100 | 34.27 | 53.3 | 1.3263 | 61.0086 | |
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| 0.0485 | 1.1166 | 10200 | 34.26 | 53.1 | 1.3319 | 60.6934 | |
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| 0.0582 | 1.1275 | 10300 | 30.37 | 51.24 | 1.3893 | 70.2837 | |
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| 0.0559 | 1.1385 | 10400 | 31.61 | 49.4 | 1.4005 | 66.0513 | |
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| 0.055 | 1.1494 | 10500 | 31.93 | 50.99 | 1.3793 | 65.0608 | |
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| 0.0612 | 1.1604 | 10600 | 33.31 | 51.91 | 1.3749 | 62.9896 | |
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| 0.0599 | 1.1713 | 10700 | 33.87 | 52.96 | 1.3679 | 61.7740 | |
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| 0.0536 | 1.1823 | 10800 | 32.54 | 51.57 | 1.3313 | 62.2692 | |
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| 0.0531 | 1.1932 | 10900 | 33.83 | 52.11 | 1.3883 | 61.9991 | |
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| 0.0582 | 1.2042 | 11000 | 33.18 | 51.63 | 1.3894 | 61.5038 | |
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| 0.0506 | 1.2151 | 11100 | 32.51 | 51.24 | 1.3338 | 63.5299 | |
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| 0.0489 | 1.2261 | 11200 | 32.95 | 51.53 | 1.3625 | 64.2053 | |
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| 0.0387 | 1.2370 | 11300 | 34.5 | 52.47 | 1.3496 | 60.4232 | |
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| 0.0512 | 1.2479 | 11400 | 34.5 | 52.72 | 1.3731 | 60.6934 | |
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| 0.0459 | 1.2589 | 11500 | 33.27 | 51.89 | 1.3655 | 62.8996 | |
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| 0.0457 | 1.2698 | 11600 | 30.26 | 49.96 | 1.3824 | 67.7623 | |
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| 0.0407 | 1.2808 | 11700 | 31.56 | 51.37 | 1.3775 | 62.9446 | |
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| 0.0396 | 1.2917 | 11800 | 34.06 | 51.91 | 1.3677 | 59.6128 | |
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| 0.0419 | 1.3027 | 11900 | 34.18 | 52.77 | 1.3648 | 60.1081 | |
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| 0.0291 | 1.3136 | 12000 | 33.9 | 51.61 | 1.3697 | 60.6934 | |
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| 0.0351 | 1.3246 | 12100 | 34.66 | 53.1 | 1.3565 | 60.5133 | |
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| 0.0329 | 1.3355 | 12200 | 33.59 | 53.0 | 1.3592 | 61.8190 | |
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| 0.0409 | 1.3465 | 12300 | 34.41 | 52.96 | 1.3690 | 59.6578 | |
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| 0.0386 | 1.3574 | 12400 | 34.68 | 53.26 | 1.3440 | 59.1175 | |
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| 0.0221 | 1.3684 | 12500 | 33.35 | 51.9 | 1.3450 | 60.3332 | |
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| 0.032 | 1.3793 | 12600 | 33.09 | 52.07 | 1.3514 | 62.3143 | |
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| 0.0364 | 1.3903 | 12700 | 34.08 | 52.49 | 1.3538 | 60.0630 | |
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| 0.024 | 1.4012 | 12800 | 34.75 | 53.14 | 1.3451 | 58.8474 | |
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| 0.0245 | 1.4122 | 12900 | 34.09 | 52.38 | 1.3544 | 59.7479 | |
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| 0.0271 | 1.4231 | 13000 | 1.3521| 34.31 | 52.5 | 59.7028 | |
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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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