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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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- ymoslem/EUbookshop-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 Medium 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, Wikimedia, and EUbookshop |
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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: 35.77 |
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- name: Wer |
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type: wer |
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value: 58.397118415128325 |
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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 |
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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, Wikimedia, and EUbookshop dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1622 |
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- Bleu: 35.77 |
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- Chrf: 56.32 |
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- Wer: 58.3971 |
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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: 15000 |
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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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| 2.6534 | 0.0138 | 100 | 1.43 | 15.99 | 2.2446 | 269.1130 | |
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| 2.4519 | 0.0276 | 200 | 2.13 | 18.36 | 2.1941 | 250.5178 | |
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| 2.2928 | 0.0414 | 300 | 7.14 | 25.95 | 2.0086 | 128.3656 | |
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| 2.233 | 0.0552 | 400 | 5.61 | 24.25 | 2.0239 | 134.0837 | |
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| 2.0406 | 0.0690 | 500 | 5.64 | 25.65 | 1.9215 | 183.8361 | |
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| 2.0273 | 0.0828 | 600 | 13.41 | 30.96 | 1.8556 | 83.7010 | |
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| 1.895 | 0.0966 | 700 | 7.02 | 26.82 | 1.8278 | 158.2170 | |
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| 1.9889 | 0.1103 | 800 | 12.22 | 31.62 | 1.7842 | 99.6398 | |
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| 1.8484 | 0.1241 | 900 | 10.97 | 30.45 | 1.7648 | 91.1751 | |
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| 1.7491 | 0.1379 | 1000 | 10.0 | 29.42 | 1.7498 | 109.0050 | |
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| 1.699 | 0.1517 | 1100 | 12.53 | 34.87 | 1.6662 | 109.9054 | |
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| 1.6959 | 0.1655 | 1200 | 14.54 | 34.8 | 1.6287 | 92.3008 | |
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| 1.6682 | 0.1793 | 1300 | 13.26 | 33.5 | 1.5800 | 103.0617 | |
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| 1.6625 | 0.1931 | 1400 | 19.71 | 37.33 | 1.6115 | 75.9118 | |
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| 1.5462 | 0.2069 | 1500 | 18.3 | 39.49 | 1.4993 | 93.7866 | |
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| 1.3834 | 0.2207 | 1600 | 20.32 | 40.87 | 1.4906 | 79.2436 | |
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| 1.39 | 0.2345 | 1700 | 17.3 | 38.16 | 1.4752 | 93.1562 | |
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| 1.5061 | 0.2483 | 1800 | 20.11 | 39.69 | 1.4004 | 81.0446 | |
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| 1.4125 | 0.2621 | 1900 | 23.82 | 42.67 | 1.3854 | 73.3904 | |
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| 1.3181 | 0.2759 | 2000 | 20.57 | 40.87 | 1.3979 | 78.8384 | |
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| 1.283 | 0.2897 | 2100 | 17.97 | 40.47 | 1.3446 | 88.8789 | |
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| 1.2061 | 0.3034 | 2200 | 25.12 | 45.42 | 1.3130 | 73.5254 | |
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| 1.2091 | 0.3172 | 2300 | 22.12 | 43.56 | 1.3274 | 79.8739 | |
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| 1.1264 | 0.3310 | 2400 | 22.94 | 45.96 | 1.2771 | 78.2080 | |
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| 1.0972 | 0.3448 | 2500 | 24.38 | 46.04 | 1.2858 | 75.4615 | |
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| 1.0822 | 0.3586 | 2600 | 27.39 | 48.34 | 1.2376 | 67.6722 | |
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| 1.0316 | 0.3724 | 2700 | 28.0 | 47.61 | 1.2461 | 68.5277 | |
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| 1.165 | 0.3862 | 2800 | 26.05 | 48.13 | 1.1869 | 71.6794 | |
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| 1.025 | 0.4 | 2900 | 27.14 | 47.91 | 1.1716 | 68.7528 | |
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| 0.8978 | 0.4138 | 3000 | 28.34 | 49.15 | 1.1628 | 65.6461 | |
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| 0.9146 | 0.4276 | 3100 | 25.81 | 48.42 | 1.1703 | 71.7244 | |
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| 0.9764 | 0.4414 | 3200 | 29.63 | 51.22 | 1.1526 | 67.3570 | |
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| 0.9455 | 0.4552 | 3300 | 25.31 | 49.73 | 1.1108 | 72.6249 | |
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| 0.9073 | 0.4690 | 3400 | 27.7 | 50.85 | 1.1085 | 72.7150 | |
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| 0.8596 | 0.4828 | 3500 | 28.34 | 52.39 | 1.0927 | 67.9424 | |
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| 0.8241 | 0.4966 | 3600 | 29.95 | 51.37 | 1.1026 | 65.2859 | |
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| 0.8436 | 0.5103 | 3700 | 27.18 | 51.45 | 1.0718 | 71.2292 | |
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| 0.8318 | 0.5241 | 3800 | 30.71 | 53.35 | 1.0678 | 64.3404 | |
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| 0.8262 | 0.5379 | 3900 | 27.05 | 51.94 | 1.0534 | 71.5894 | |
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| 0.8129 | 0.5517 | 4000 | 27.38 | 51.97 | 1.0491 | 72.1747 | |
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| 0.9036 | 0.5655 | 4100 | 14.43 | 40.57 | 1.2250 | 139.3066 | |
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| 1.0314 | 0.5793 | 4200 | 24.27 | 46.97 | 1.2310 | 75.5966 | |
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| 0.9209 | 0.5931 | 4300 | 23.55 | 46.04 | 1.2447 | 76.4070 | |
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| 0.9204 | 0.6069 | 4400 | 25.87 | 45.32 | 1.2891 | 73.0302 | |
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| 0.9843 | 0.6207 | 4500 | 27.2 | 46.36 | 1.2269 | 71.8145 | |
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| 1.0225 | 0.6345 | 4600 | 26.16 | 45.72 | 1.2403 | 69.6983 | |
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| 0.9773 | 0.6483 | 4700 | 26.37 | 45.62 | 1.2464 | 68.4376 | |
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| 0.9794 | 0.6621 | 4800 | 24.77 | 47.11 | 1.2461 | 72.0846 | |
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| 0.8905 | 0.6759 | 4900 | 24.58 | 46.35 | 1.2345 | 71.2742 | |
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| 0.8305 | 0.6897 | 5000 | 27.28 | 48.37 | 1.2239 | 68.1675 | |
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| 0.9019 | 0.7034 | 5100 | 27.04 | 50.28 | 1.1730 | 70.1486 | |
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| 0.7969 | 0.7172 | 5200 | 26.27 | 48.07 | 1.1807 | 69.0230 | |
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| 0.8036 | 0.7310 | 5300 | 23.04 | 48.3 | 1.1632 | 77.5326 | |
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| 0.8195 | 0.7448 | 5400 | 25.58 | 50.29 | 1.1811 | 76.2269 | |
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| 0.7697 | 0.7586 | 5500 | 23.99 | 48.91 | 1.1825 | 81.4948 | |
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| 0.727 | 0.7724 | 5600 | 23.93 | 49.23 | 1.1623 | 79.5137 | |
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| 0.8002 | 0.7862 | 5700 | 26.29 | 50.44 | 1.1503 | 75.6866 | |
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| 0.6909 | 0.8 | 5800 | 29.27 | 50.85 | 1.1338 | 64.0252 | |
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| 0.7146 | 0.8138 | 5900 | 28.24 | 50.82 | 1.1420 | 66.6367 | |
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| 0.7452 | 0.8276 | 6000 | 31.33 | 51.92 | 1.1328 | 62.4944 | |
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| 0.5989 | 0.8414 | 6100 | 31.1 | 52.15 | 1.1455 | 65.1959 | |
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| 0.6818 | 0.8552 | 6200 | 32.56 | 52.46 | 1.1112 | 62.1342 | |
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| 0.6074 | 0.8690 | 6300 | 33.48 | 53.32 | 1.1072 | 60.6033 | |
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| 0.5942 | 0.8828 | 6400 | 31.39 | 51.03 | 1.1462 | 62.8546 | |
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| 0.6341 | 0.8966 | 6500 | 31.55 | 52.15 | 1.1093 | 62.4043 | |
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| 0.5992 | 0.9103 | 6600 | 33.06 | 52.52 | 1.1215 | 61.4588 | |
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| 0.6156 | 0.9241 | 6700 | 32.38 | 52.76 | 1.1031 | 62.9446 | |
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| 0.6169 | 0.9379 | 6800 | 31.46 | 52.96 | 1.1082 | 64.3404 | |
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| 0.6543 | 0.9517 | 6900 | 33.49 | 54.02 | 1.0943 | 63.1247 | |
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| 0.5017 | 0.9655 | 7000 | 30.95 | 52.64 | 1.1141 | 68.6177 | |
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| 0.5583 | 0.9793 | 7100 | 34.39 | 54.03 | 1.1004 | 61.6839 | |
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| 0.5986 | 0.9931 | 7200 | 33.92 | 52.85 | 1.1055 | 62.4944 | |
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| 0.2443 | 1.0069 | 7300 | 34.86 | 53.01 | 1.1442 | 60.1981 | |
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| 0.254 | 1.0207 | 7400 | 33.92 | 53.25 | 1.1458 | 62.1792 | |
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| 0.2827 | 1.0345 | 7500 | 34.49 | 53.43 | 1.1190 | 60.6484 | |
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| 0.2326 | 1.0483 | 7600 | 35.47 | 53.53 | 1.1237 | 59.2076 | |
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| 0.2017 | 1.0621 | 7700 | 34.65 | 53.87 | 1.1179 | 60.0180 | |
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| 0.2367 | 1.0759 | 7800 | 34.23 | 53.67 | 1.1075 | 60.6484 | |
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| 0.2276 | 1.0897 | 7900 | 34.67 | 54.51 | 1.1063 | 60.3332 | |
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| 0.2087 | 1.1034 | 8000 | 34.44 | 54.07 | 1.1090 | 60.6484 | |
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| 0.2514 | 1.1172 | 8100 | 29.85 | 51.91 | 1.1199 | 69.6083 | |
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| 0.2692 | 1.1310 | 8200 | 28.05 | 51.94 | 1.1642 | 72.1747 | |
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| 0.2784 | 1.1448 | 8300 | 27.26 | 50.77 | 1.1262 | 74.8312 | |
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| 0.2539 | 1.1586 | 8400 | 30.7 | 53.1 | 1.1463 | 65.0158 | |
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| 0.2599 | 1.1724 | 8500 | 31.64 | 53.71 | 1.1255 | 63.2148 | |
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| 0.2419 | 1.1862 | 8600 | 33.2 | 54.15 | 1.1223 | 62.4043 | |
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| 0.2583 | 1.2 | 8700 | 33.98 | 53.65 | 1.1304 | 61.2787 | |
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| 0.239 | 1.2138 | 8800 | 34.68 | 54.35 | 1.1371 | 61.7740 | |
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| 0.2198 | 1.2276 | 8900 | 30.65 | 52.15 | 1.1533 | 72.2647 | |
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| 0.248 | 1.2414 | 9000 | 31.98 | 53.68 | 1.1266 | 65.4210 | |
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| 0.2377 | 1.2552 | 9100 | 30.9 | 53.6 | 1.1510 | 67.9424 | |
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| 0.2183 | 1.2690 | 9200 | 30.35 | 53.04 | 1.1565 | 73.1202 | |
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| 0.1999 | 1.2828 | 9300 | 29.48 | 53.0 | 1.1426 | 74.2909 | |
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| 0.22 | 1.2966 | 9400 | 31.93 | 53.16 | 1.1332 | 66.1414 | |
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| 0.2063 | 1.3103 | 9500 | 32.42 | 53.79 | 1.1144 | 63.3949 | |
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| 0.2054 | 1.3241 | 9600 | 33.64 | 54.69 | 1.1146 | 61.5038 | |
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| 0.2145 | 1.3379 | 9700 | 36.68 | 55.64 | 1.1123 | 57.5867 | |
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| 0.2059 | 1.3517 | 9800 | 36.93 | 56.15 | 1.1102 | 57.5416 | |
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| 0.2001 | 1.3655 | 9900 | 36.4 | 56.09 | 1.1143 | 57.9469 | |
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| 0.1973 | 1.3793 | 10000 | 36.46 | 55.74 | 1.1121 | 58.2620 | |
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| 0.2184 | 1.3931 | 10100 | 1.1377| 31.31 | 53.89 | 66.9068 | |
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| 0.324 | 1.4069 | 10200 | 1.1906| 29.38 | 51.17 | 70.2386 | |
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| 0.3419 | 1.4207 | 10300 | 1.2105| 32.38 | 52.69 | 63.3498 | |
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| 0.2838 | 1.4345 | 10400 | 1.1928| 31.53 | 50.99 | 63.5299 | |
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| 0.2888 | 1.4483 | 10500 | 1.2374| 26.67 | 49.63 | 72.6700 | |
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| 0.3196 | 1.4621 | 10600 | 1.2343| 26.79 | 48.63 | 72.3998 | |
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| 0.3081 | 1.4759 | 10700 | 1.2136| 26.4 | 49.29 | 74.0207 | |
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| 0.2861 | 1.4897 | 10800 | 1.1898| 26.01 | 50.26 | 73.2553 | |
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| 0.2951 | 1.5034 | 10900 | 1.2020| 28.59 | 51.08 | 68.0774 | |
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| 0.2637 | 1.5172 | 11000 | 1.1516| 29.92 | 51.81 | 66.4566 | |
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| 0.2854 | 1.5310 | 11100 | 1.1791| 27.96 | 50.76 | 72.7150 | |
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| 0.2959 | 1.5448 | 11200 | 1.1705| 30.01 | 51.37 | 65.5110 | |
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| 0.2649 | 1.5586 | 11300 | 1.1934| 24.87 | 49.47 | 79.0185 | |
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| 0.2667 | 1.5724 | 11400 | 1.1785| 29.03 | 50.83 | 69.2481 | |
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| 0.276 | 1.5862 | 11500 | 1.1887| 29.83 | 52.07 | 66.8618 | |
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| 0.2588 | 1.6 | 11600 | 1.1778| 30.0 | 52.37 | 66.9518 | |
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| 0.2669 | 1.6138 | 11700 | 1.1858| 31.38 | 51.74 | 63.4399 | |
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| 0.2472 | 1.6276 | 11800 | 1.1927| 31.14 | 50.61 | 64.4755 | |
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| 0.2477 | 1.6414 | 11900 | 1.2052| 27.75 | 51.33 | 68.1225 | |
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| 0.2327 | 1.6552 | 12000 | 1.1935| 29.36 | 51.86 | 67.7623 | |
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| 0.2299 | 1.6690 | 12100 | 1.1804| 27.2 | 51.18 | 76.8122 | |
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| 0.2244 | 1.6828 | 12200 | 1.2038| 29.6 | 52.19 | 67.4471 | |
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| 0.225 | 1.6966 | 12300 | 1.1762| 31.87 | 53.47 | 64.1603 | |
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| 0.2219 | 1.7103 | 12400 | 1.1784| 31.75 | 51.76 | 65.1959 | |
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| 0.2216 | 1.7241 | 12500 | 1.1717| 31.69 | 53.61 | 62.8546 | |
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| 0.2646 | 1.7379 | 12600 | 1.1463| 32.85 | 51.95 | 60.0630 | |
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| 0.204 | 1.7517 | 12700 | 1.1438| 33.17 | 54.96 | 60.1531 | |
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| 0.19 | 1.7655 | 12800 | 1.1733| 31.62 | 53.57 | 63.1247 | |
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| 0.2 | 1.7793 | 12900 | 1.1616| 32.16 | 53.05 | 62.1792 | |
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| 0.1813 | 1.7931 | 13000 | 1.1632| 30.8 | 52.56 | 63.9802 | |
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| 0.1648 | 1.8069 | 13100 | 1.1631| 31.47 | 52.44 | 62.5844 | |
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| 0.1972 | 1.8207 | 13200 | 1.1591| 34.03 | 54.33 | 59.6128 | |
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| 0.1648 | 1.8345 | 13300 | 1.1513| 33.92 | 53.52 | 61.1887 | |
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| 0.1871 | 1.8483 | 13400 | 1.1571| 33.33 | 53.79 | 62.5844 | |
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| 0.1762 | 1.8621 | 13500 | 1.1422| 34.34 | 54.64 | 60.7834 | |
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| 0.1984 | 1.8759 | 13600 | 1.1465| 33.58 | 55.31 | 62.3593 | |
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| 0.1838 | 1.8897 | 13700 | 1.1355| 34.84 | 56.04 | 59.9730 | |
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| 0.1337 | 1.9034 | 13800 | 1.1309| 34.3 | 55.84 | 60.5133 | |
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| 0.1692 | 1.9172 | 13900 | 1.1407| 33.62 | 55.48 | 62.9896 | |
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| 0.1556 | 1.9310 | 14000 | 1.1484| 35.42 | 55.56 | 59.0725 | |
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| 0.1364 | 1.9448 | 14100 | 1.1440| 34.44 | 55.35 | 59.9280 | |
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| 0.1401 | 1.9586 | 14200 | 1.1345| 33.77 | 55.22 | 60.5133 | |
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| 0.1399 | 1.9724 | 14300 | 1.1376| 35.04 | 55.47 | 59.3877 | |
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| 0.139 | 1.9862 | 14400 | 1.1337| 35.58 | 56.38 | 58.0369 | |
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| 0.1523 | 2.0 | 14500 | 1.1349| 35.24 | 55.73 | 59.3877 | |
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| 0.0799 | 2.0138 | 14600 | 1.1575| 35.13 | 56.17 | 59.7479 | |
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| 0.06 | 2.0276 | 14700 | 1.1582| 35.52 | 56.5 | 59.4327 | |
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| 0.0583 | 2.0414 | 14800 | 1.1628| 35.65 | 56.55 | 58.6673 | |
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| 0.0605 | 2.0552 | 14900 | 1.1615| 35.85 | 56.37 | 58.0819 | |
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| 0.0654 | 2.0690 | 15000 | 1.1622| 35.77 | 56.32 | 58.3971 | |
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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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