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sqrk
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uaspeech-mms1ball-Nov30

Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +159 -7
  2. adapter.uaspeech-eng.safetensors +1 -1
  3. model.safetensors +1 -1
README.md CHANGED
@@ -3,6 +3,8 @@ license: cc-by-nc-4.0
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  base_model: facebook/mms-1b-all
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: uaspeech-mms1ball-Nov30
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  results: []
@@ -15,13 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 1.1373
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- - eval_wer: 0.5222
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- - eval_runtime: 219.0768
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- - eval_samples_per_second: 23.978
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- - eval_steps_per_second: 5.998
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- - epoch: 0.9455
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- - step: 14900
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  ## Model description
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@@ -50,6 +47,161 @@ The following hyperparameters were used during training:
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  - num_epochs: 100
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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  - Transformers 4.43.4
 
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  base_model: facebook/mms-1b-all
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - wer
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  model-index:
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  - name: uaspeech-mms1ball-Nov30
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  results: []
 
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  This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1373
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+ - Wer: 0.5222
 
 
 
 
 
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  ## Model description
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  - num_epochs: 100
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  - mixed_precision_training: Native AMP
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:-----:|:---------------:|:------:|
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+ | 45.2252 | 0.0063 | 100 | 3.7562 | 1.0 |
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+ | 2.9851 | 0.0127 | 200 | 2.0328 | 0.8281 |
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+ | 2.0067 | 0.0190 | 300 | 1.8614 | 0.6848 |
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+ | 2.1249 | 0.0254 | 400 | 2.0929 | 0.7247 |
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+ | 1.8786 | 0.0317 | 500 | 1.6966 | 0.6522 |
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+ | 1.8295 | 0.0381 | 600 | 1.6550 | 0.6579 |
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+ | 1.8186 | 0.0444 | 700 | 1.6961 | 0.6457 |
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+ | 1.839 | 0.0508 | 800 | 1.7019 | 0.6642 |
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+ | 1.8854 | 0.0571 | 900 | 1.6492 | 0.6455 |
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+ | 2.0186 | 0.0635 | 1000 | 1.5746 | 0.6682 |
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+ | 1.8061 | 0.0698 | 1100 | 1.5590 | 0.6345 |
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+ | 1.6994 | 0.0761 | 1200 | 1.6544 | 0.6509 |
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+ | 1.6444 | 0.0825 | 1300 | 1.6297 | 0.6115 |
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+ | 1.7308 | 0.0888 | 1400 | 1.7002 | 0.6337 |
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+ | 1.8179 | 0.0952 | 1500 | 1.5325 | 0.6179 |
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+ | 1.7174 | 0.1015 | 1600 | 1.5668 | 0.6343 |
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+ | 1.7043 | 0.1079 | 1700 | 1.5762 | 0.6415 |
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+ | 1.5174 | 0.1142 | 1800 | 1.4478 | 0.5991 |
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+ | 1.6108 | 0.1206 | 1900 | 1.4394 | 0.6054 |
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+ | 1.6227 | 0.1269 | 2000 | 1.5185 | 0.5964 |
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+ | 1.773 | 0.1333 | 2100 | 1.6450 | 0.6124 |
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+ | 1.6231 | 0.1396 | 2200 | 1.3599 | 0.6016 |
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+ | 1.6005 | 0.1459 | 2300 | 1.3782 | 0.5943 |
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+ | 1.524 | 0.1523 | 2400 | 1.6099 | 0.5953 |
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+ | 1.5881 | 0.1586 | 2500 | 1.4681 | 0.6160 |
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+ | 1.5577 | 0.1650 | 2600 | 1.3934 | 0.6052 |
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+ | 1.5556 | 0.1713 | 2700 | 1.3960 | 0.6099 |
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+ | 1.609 | 0.1777 | 2800 | 1.4837 | 0.6008 |
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+ | 1.3661 | 0.1840 | 2900 | 1.2992 | 0.5800 |
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+ | 1.4908 | 0.1904 | 3000 | 1.3942 | 0.5844 |
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+ | 1.6022 | 0.1967 | 3100 | 1.4685 | 0.5907 |
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+ | 1.7082 | 0.2031 | 3200 | 1.4685 | 0.6214 |
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+ | 1.5526 | 0.2094 | 3300 | 1.4331 | 0.6038 |
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+ | 1.4424 | 0.2157 | 3400 | 1.3674 | 0.5791 |
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+ | 1.3544 | 0.2221 | 3500 | 1.3960 | 0.5882 |
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+ | 1.4868 | 0.2284 | 3600 | 1.3507 | 0.5882 |
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+ | 1.5313 | 0.2348 | 3700 | 1.5923 | 0.5764 |
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+ | 1.5763 | 0.2411 | 3800 | 1.3493 | 0.5681 |
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+ | 1.3742 | 0.2475 | 3900 | 1.3979 | 0.5827 |
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+ | 1.5003 | 0.2538 | 4000 | 1.4011 | 0.5886 |
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+ | 1.5894 | 0.2602 | 4100 | 1.3652 | 0.5519 |
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+ | 1.5496 | 0.2665 | 4200 | 1.2970 | 0.5860 |
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+ | 1.6228 | 0.2729 | 4300 | 1.4056 | 0.5753 |
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+ | 1.4173 | 0.2792 | 4400 | 1.3485 | 0.5515 |
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+ | 1.5236 | 0.2856 | 4500 | 1.2558 | 0.5473 |
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+ | 1.3976 | 0.2919 | 4600 | 1.3535 | 0.5505 |
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+ | 1.4656 | 0.2982 | 4700 | 1.3634 | 0.5865 |
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+ | 1.4089 | 0.3046 | 4800 | 1.3172 | 0.5458 |
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+ | 1.2844 | 0.3109 | 4900 | 1.3553 | 0.5606 |
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+ | 1.3984 | 0.3173 | 5000 | 1.2458 | 0.5679 |
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+ | 1.4784 | 0.3236 | 5100 | 1.3808 | 0.5484 |
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+ | 1.4339 | 0.3300 | 5200 | 1.3194 | 0.5578 |
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+ | 1.6029 | 0.3363 | 5300 | 1.3393 | 0.5631 |
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+ | 1.4778 | 0.3427 | 5400 | 1.3053 | 0.5639 |
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+ | 1.5093 | 0.3490 | 5500 | 1.2234 | 0.5445 |
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+ | 1.5348 | 0.3554 | 5600 | 1.2514 | 0.5583 |
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+ | 1.5195 | 0.3617 | 5700 | 1.2954 | 0.5561 |
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+ | 1.5035 | 0.3680 | 5800 | 1.1854 | 0.5435 |
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+ | 1.532 | 0.3744 | 5900 | 1.2768 | 0.5486 |
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+ | 1.5833 | 0.3807 | 6000 | 1.3575 | 0.5547 |
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+ | 1.4789 | 0.3871 | 6100 | 1.2984 | 0.5418 |
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+ | 1.3557 | 0.3934 | 6200 | 1.2763 | 0.5326 |
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+ | 1.2738 | 0.3998 | 6300 | 1.3761 | 0.5351 |
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+ | 1.454 | 0.4061 | 6400 | 1.3057 | 0.5325 |
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+ | 1.403 | 0.4125 | 6500 | 1.3707 | 0.5662 |
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+ | 1.5306 | 0.4188 | 6600 | 1.3330 | 0.5583 |
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+ | 1.4576 | 0.4252 | 6700 | 1.2403 | 0.5349 |
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+ | 1.4214 | 0.4315 | 6800 | 1.3175 | 0.5363 |
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+ | 1.5853 | 0.4378 | 6900 | 1.2071 | 0.5281 |
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+ | 1.522 | 0.4442 | 7000 | 1.2593 | 0.5387 |
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+ | 1.2743 | 0.4505 | 7100 | 1.3154 | 0.5549 |
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+ | 1.3778 | 0.4569 | 7200 | 1.2544 | 0.5365 |
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+ | 1.2875 | 0.4632 | 7300 | 1.2312 | 0.5281 |
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+ | 1.3484 | 0.4696 | 7400 | 1.2599 | 0.5340 |
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+ | 1.5618 | 0.4759 | 7500 | 1.3038 | 0.5568 |
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+ | 1.4391 | 0.4823 | 7600 | 1.2523 | 0.5355 |
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+ | 1.4676 | 0.4886 | 7700 | 1.2205 | 0.5311 |
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+ | 1.371 | 0.4950 | 7800 | 1.1996 | 0.5275 |
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+ | 1.361 | 0.5013 | 7900 | 1.1635 | 0.5186 |
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+ | 1.463 | 0.5076 | 8000 | 1.2232 | 0.5344 |
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+ | 1.348 | 0.5140 | 8100 | 1.1407 | 0.5174 |
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+ | 1.4943 | 0.5203 | 8200 | 1.3098 | 0.5361 |
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+ | 1.3703 | 0.5267 | 8300 | 1.1393 | 0.5226 |
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+ | 1.4188 | 0.5330 | 8400 | 1.1914 | 0.4995 |
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+ | 1.3048 | 0.5394 | 8500 | 1.1555 | 0.5170 |
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+ | 1.4468 | 0.5457 | 8600 | 1.1515 | 0.5149 |
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+ | 1.2279 | 0.5521 | 8700 | 1.2047 | 0.5168 |
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+ | 1.2367 | 0.5584 | 8800 | 1.1868 | 0.5208 |
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+ | 1.3536 | 0.5648 | 8900 | 1.1398 | 0.5189 |
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+ | 1.3496 | 0.5711 | 9000 | 1.2705 | 0.5176 |
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+ | 1.4915 | 0.5774 | 9100 | 1.2007 | 0.5079 |
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+ | 1.474 | 0.5838 | 9200 | 1.2192 | 0.5378 |
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+ | 1.3093 | 0.5901 | 9300 | 1.1065 | 0.5125 |
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+ | 1.1994 | 0.5965 | 9400 | 1.2120 | 0.5201 |
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+ | 1.502 | 0.6028 | 9500 | 1.1464 | 0.5290 |
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+ | 1.5327 | 0.6092 | 9600 | 1.2010 | 0.5384 |
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+ | 1.4533 | 0.6155 | 9700 | 1.1614 | 0.5146 |
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+ | 1.4554 | 0.6219 | 9800 | 1.1353 | 0.5155 |
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+ | 1.3605 | 0.6282 | 9900 | 1.1788 | 0.5058 |
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+ | 1.3606 | 0.6346 | 10000 | 1.1877 | 0.5178 |
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+ | 1.3295 | 0.6409 | 10100 | 1.2601 | 0.5452 |
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+ | 1.4172 | 0.6472 | 10200 | 1.1926 | 0.5083 |
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+ | 1.4859 | 0.6536 | 10300 | 1.1426 | 0.5077 |
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+ | 1.5264 | 0.6599 | 10400 | 1.1495 | 0.5121 |
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+ | 1.3455 | 0.6663 | 10500 | 1.1535 | 0.5140 |
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+ | 1.2375 | 0.6726 | 10600 | 1.1857 | 0.5087 |
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+ | 1.2808 | 0.6790 | 10700 | 1.2156 | 0.5005 |
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+ | 1.3358 | 0.6853 | 10800 | 1.1543 | 0.5075 |
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+ | 1.361 | 0.6917 | 10900 | 1.2553 | 0.5290 |
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+ | 1.3859 | 0.6980 | 11000 | 1.1458 | 0.5245 |
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+ | 1.5061 | 0.7044 | 11100 | 1.1547 | 0.5399 |
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+ | 1.2777 | 0.7107 | 11200 | 1.1677 | 0.5180 |
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+ | 1.2645 | 0.7171 | 11300 | 1.2715 | 0.5191 |
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+ | 1.3514 | 0.7234 | 11400 | 1.1811 | 0.5109 |
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+ | 1.2733 | 0.7297 | 11500 | 1.1079 | 0.5134 |
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+ | 1.2961 | 0.7361 | 11600 | 1.3171 | 0.5188 |
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+ | 1.3744 | 0.7424 | 11700 | 1.1271 | 0.5106 |
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+ | 1.2626 | 0.7488 | 11800 | 1.0821 | 0.5001 |
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+ | 1.317 | 0.7551 | 11900 | 1.1156 | 0.5037 |
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+ | 1.1732 | 0.7615 | 12000 | 1.1828 | 0.5287 |
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+ | 1.3693 | 0.7678 | 12100 | 1.1063 | 0.5172 |
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+ | 1.3227 | 0.7742 | 12200 | 1.1450 | 0.4948 |
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+ | 1.41 | 0.7805 | 12300 | 1.0917 | 0.5079 |
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+ | 1.2909 | 0.7869 | 12400 | 1.1321 | 0.5066 |
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+ | 1.1509 | 0.7932 | 12500 | 1.1678 | 0.4921 |
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+ | 1.3629 | 0.7995 | 12600 | 1.1482 | 0.4923 |
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+ | 1.2959 | 0.8059 | 12700 | 1.1488 | 0.5064 |
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+ | 1.3537 | 0.8122 | 12800 | 1.1356 | 0.5014 |
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+ | 1.1468 | 0.8186 | 12900 | 1.0872 | 0.4970 |
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+ | 1.3582 | 0.8249 | 13000 | 1.1221 | 0.4913 |
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+ | 1.3872 | 0.8313 | 13100 | 1.2243 | 0.4925 |
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+ | 1.4433 | 0.8376 | 13200 | 1.1536 | 0.5205 |
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+ | 1.4121 | 0.8440 | 13300 | 1.1322 | 0.5050 |
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+ | 1.0979 | 0.8503 | 13400 | 1.1252 | 0.4927 |
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+ | 1.3989 | 0.8567 | 13500 | 1.0632 | 0.5035 |
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+ | 1.1527 | 0.8630 | 13600 | 1.1041 | 0.4942 |
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+ | 1.167 | 0.8693 | 13700 | 1.0895 | 0.4913 |
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+ | 1.3945 | 0.8757 | 13800 | 1.1256 | 0.5050 |
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+ | 1.2615 | 0.8820 | 13900 | 1.1768 | 0.5226 |
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+ | 1.3221 | 0.8884 | 14000 | 1.2068 | 0.5050 |
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+ | 1.4254 | 0.8947 | 14100 | 1.1757 | 0.5028 |
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+ | 1.1403 | 0.9011 | 14200 | 1.1589 | 0.5161 |
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+ | 1.304 | 0.9074 | 14300 | 1.1399 | 0.5140 |
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+ | 1.3728 | 0.9138 | 14400 | 1.0997 | 0.5132 |
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+ | 1.4233 | 0.9201 | 14500 | 1.0702 | 0.4948 |
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+ | 1.1177 | 0.9265 | 14600 | 1.0930 | 0.4936 |
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+ | 1.186 | 0.9328 | 14700 | 1.1956 | 0.4919 |
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+ | 1.3834 | 0.9391 | 14800 | 1.1244 | 0.5007 |
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+ | 1.3236 | 0.9455 | 14900 | 1.1373 | 0.5222 |
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+
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+
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  ### Framework versions
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  - Transformers 4.43.4
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