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ssc-ruc-mms-model-mix-adapt-max3-devtrain

Automatic Speech Recognition
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Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +25 -85
  2. adapter.ruc.safetensors +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,7 +1,5 @@
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  ---
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  library_name: transformers
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- 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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  metrics:
@@ -16,11 +14,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # ssc-ruc-mms-model-mix-adapt-max3-devtrain
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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: 0.4248
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- - Cer: 0.1349
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- - Wer: 0.5697
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  ## Model description
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@@ -40,95 +38,37 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0005
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- - train_batch_size: 8
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  - eval_batch_size: 6
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  - seed: 42
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  - gradient_accumulation_steps: 2
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- - total_train_batch_size: 16
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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- - num_epochs: 20
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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 | Cer | Wer |
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- |:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
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- | 1.0456 | 0.2674 | 200 | 0.7005 | 0.1876 | 0.7348 |
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- | 0.9305 | 0.5348 | 400 | 0.6500 | 0.1789 | 0.7143 |
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- | 0.9102 | 0.8021 | 600 | 0.6226 | 0.1716 | 0.6959 |
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- | 0.8748 | 1.0695 | 800 | 0.5937 | 0.1650 | 0.6777 |
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- | 0.8449 | 1.3369 | 1000 | 0.5832 | 0.1629 | 0.6735 |
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- | 0.8468 | 1.6043 | 1200 | 0.5809 | 0.1629 | 0.6763 |
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- | 0.8773 | 1.8717 | 1400 | 0.5673 | 0.1611 | 0.6642 |
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- | 0.842 | 2.1390 | 1600 | 0.5611 | 0.1586 | 0.6618 |
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- | 0.8072 | 2.4064 | 1800 | 0.5468 | 0.1536 | 0.6484 |
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- | 0.8458 | 2.6738 | 2000 | 0.5488 | 0.1543 | 0.6403 |
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- | 0.8067 | 2.9412 | 2200 | 0.5323 | 0.1571 | 0.6530 |
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- | 0.8039 | 3.2086 | 2400 | 0.5307 | 0.1556 | 0.6467 |
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- | 0.7867 | 3.4759 | 2600 | 0.5273 | 0.1519 | 0.6353 |
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- | 0.802 | 3.7433 | 2800 | 0.5372 | 0.1537 | 0.6461 |
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- | 0.8293 | 4.0107 | 3000 | 0.5359 | 0.1552 | 0.6490 |
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- | 0.7776 | 4.2781 | 3200 | 0.5194 | 0.1542 | 0.6411 |
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- | 0.7744 | 4.5455 | 3400 | 0.5169 | 0.1512 | 0.6353 |
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- | 0.7815 | 4.8128 | 3600 | 0.5188 | 0.1530 | 0.6397 |
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- | 0.75 | 5.0802 | 3800 | 0.5100 | 0.1518 | 0.6291 |
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- | 0.7806 | 5.3476 | 4000 | 0.5020 | 0.1482 | 0.6220 |
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- | 0.7466 | 5.6150 | 4200 | 0.5074 | 0.1523 | 0.6365 |
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- | 0.7769 | 5.8824 | 4400 | 0.5069 | 0.1500 | 0.6262 |
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- | 0.716 | 6.1497 | 4600 | 0.5062 | 0.1514 | 0.6285 |
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- | 0.7188 | 6.4171 | 4800 | 0.4985 | 0.1473 | 0.6136 |
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- | 0.7666 | 6.6845 | 5000 | 0.4906 | 0.1461 | 0.6161 |
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- | 0.7389 | 6.9519 | 5200 | 0.4812 | 0.1464 | 0.6111 |
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- | 0.7356 | 7.2193 | 5400 | 0.4934 | 0.1458 | 0.6193 |
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- | 0.7315 | 7.4866 | 5600 | 0.4823 | 0.1452 | 0.6067 |
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- | 0.7446 | 7.7540 | 5800 | 0.4818 | 0.1455 | 0.6115 |
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- | 0.7463 | 8.0214 | 6000 | 0.4883 | 0.1455 | 0.6085 |
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- | 0.715 | 8.2888 | 6200 | 0.4849 | 0.1452 | 0.6092 |
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- | 0.7065 | 8.5561 | 6400 | 0.4759 | 0.1442 | 0.6026 |
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- | 0.717 | 8.8235 | 6600 | 0.4707 | 0.1433 | 0.5998 |
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- | 0.7102 | 9.0909 | 6800 | 0.4627 | 0.1420 | 0.6038 |
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- | 0.6856 | 9.3583 | 7000 | 0.4647 | 0.1414 | 0.5957 |
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- | 0.7235 | 9.6257 | 7200 | 0.4651 | 0.1425 | 0.6086 |
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- | 0.6834 | 9.8930 | 7400 | 0.4635 | 0.1413 | 0.5982 |
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- | 0.6923 | 10.1604 | 7600 | 0.4642 | 0.1414 | 0.5999 |
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- | 0.7048 | 10.4278 | 7800 | 0.4643 | 0.1419 | 0.5944 |
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- | 0.6968 | 10.6952 | 8000 | 0.4584 | 0.1397 | 0.5960 |
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- | 0.7231 | 10.9626 | 8200 | 0.4611 | 0.1414 | 0.6021 |
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- | 0.6572 | 11.2299 | 8400 | 0.4579 | 0.1404 | 0.5964 |
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- | 0.6755 | 11.4973 | 8600 | 0.4573 | 0.1394 | 0.5914 |
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- | 0.6942 | 11.7647 | 8800 | 0.4512 | 0.1394 | 0.5889 |
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- | 0.6712 | 12.0321 | 9000 | 0.4499 | 0.1395 | 0.5910 |
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- | 0.6926 | 12.2995 | 9200 | 0.4522 | 0.1380 | 0.5823 |
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- | 0.6955 | 12.5668 | 9400 | 0.4623 | 0.1423 | 0.6001 |
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- | 0.6834 | 12.8342 | 9600 | 0.4494 | 0.1381 | 0.5847 |
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- | 0.6262 | 13.1016 | 9800 | 0.4451 | 0.1379 | 0.5866 |
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- | 0.6621 | 13.3690 | 10000 | 0.4454 | 0.1384 | 0.5841 |
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- | 0.6614 | 13.6364 | 10200 | 0.4460 | 0.1383 | 0.5886 |
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- | 0.6656 | 13.9037 | 10400 | 0.4423 | 0.1366 | 0.5784 |
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- | 0.6491 | 14.1711 | 10600 | 0.4418 | 0.1375 | 0.5815 |
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- | 0.6288 | 14.4385 | 10800 | 0.4436 | 0.1367 | 0.5761 |
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- | 0.6544 | 14.7059 | 11000 | 0.4349 | 0.1360 | 0.5767 |
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- | 0.6391 | 14.9733 | 11200 | 0.4369 | 0.1360 | 0.5738 |
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- | 0.6572 | 15.2406 | 11400 | 0.4402 | 0.1354 | 0.5772 |
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- | 0.6427 | 15.5080 | 11600 | 0.4383 | 0.1357 | 0.5733 |
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- | 0.6382 | 15.7754 | 11800 | 0.4360 | 0.1361 | 0.5727 |
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- | 0.6314 | 16.0428 | 12000 | 0.4368 | 0.1359 | 0.5743 |
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- | 0.6525 | 16.3102 | 12200 | 0.4375 | 0.1354 | 0.5742 |
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- | 0.6267 | 16.5775 | 12400 | 0.4325 | 0.1351 | 0.5713 |
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- | 0.6299 | 16.8449 | 12600 | 0.4336 | 0.1348 | 0.5703 |
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- | 0.6261 | 17.1123 | 12800 | 0.4294 | 0.1356 | 0.5758 |
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- | 0.6182 | 17.3797 | 13000 | 0.4301 | 0.1356 | 0.5701 |
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- | 0.6048 | 17.6471 | 13200 | 0.4311 | 0.1360 | 0.5743 |
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- | 0.634 | 17.9144 | 13400 | 0.4303 | 0.1344 | 0.5644 |
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- | 0.6001 | 18.1818 | 13600 | 0.4289 | 0.1363 | 0.5727 |
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- | 0.6674 | 18.4492 | 13800 | 0.4282 | 0.1351 | 0.5697 |
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- | 0.6198 | 18.7166 | 14000 | 0.4261 | 0.1342 | 0.5656 |
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- | 0.6218 | 18.9840 | 14200 | 0.4255 | 0.1354 | 0.5699 |
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- | 0.6215 | 19.2513 | 14400 | 0.4254 | 0.1354 | 0.5708 |
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- | 0.6267 | 19.5187 | 14600 | 0.4250 | 0.1345 | 0.5676 |
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- | 0.6536 | 19.7861 | 14800 | 0.4248 | 0.1349 | 0.5697 |
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  ### Framework versions
 
1
  ---
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  library_name: transformers
 
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
14
 
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  # ssc-ruc-mms-model-mix-adapt-max3-devtrain
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+ This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4251
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+ - Cer: 0.1371
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+ - Wer: 0.5761
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23
  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0005
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+ - train_batch_size: 1
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  - eval_batch_size: 6
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  - seed: 42
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  - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 2
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 5
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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 | Cer | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | 0.4996 | 0.2972 | 200 | 0.4369 | 0.1393 | 0.5967 |
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+ | 0.432 | 0.5944 | 400 | 0.4474 | 0.1428 | 0.5980 |
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+ | 0.4283 | 0.8915 | 600 | 0.4476 | 0.1432 | 0.5990 |
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+ | 0.501 | 1.1887 | 800 | 0.4384 | 0.1404 | 0.5962 |
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+ | 0.4071 | 1.4859 | 1000 | 0.4414 | 0.1402 | 0.5942 |
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+ | 0.4261 | 1.7831 | 1200 | 0.4387 | 0.1394 | 0.5916 |
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+ | 0.4046 | 2.0802 | 1400 | 0.4434 | 0.1416 | 0.5928 |
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+ | 0.4214 | 2.3774 | 1600 | 0.4495 | 0.1396 | 0.5932 |
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+ | 0.364 | 2.6746 | 1800 | 0.4416 | 0.1385 | 0.5839 |
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+ | 0.4308 | 2.9718 | 2000 | 0.4304 | 0.1401 | 0.5847 |
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+ | 0.3437 | 3.2689 | 2200 | 0.4393 | 0.1388 | 0.5825 |
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+ | 0.4251 | 3.5661 | 2400 | 0.4273 | 0.1386 | 0.5795 |
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+ | 0.5201 | 3.8633 | 2600 | 0.4277 | 0.1367 | 0.5727 |
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+ | 0.3671 | 4.1605 | 2800 | 0.4273 | 0.1374 | 0.5743 |
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+ | 0.4012 | 4.4577 | 3000 | 0.4275 | 0.1362 | 0.5713 |
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+ | 0.3537 | 4.7548 | 3200 | 0.4251 | 0.1371 | 0.5761 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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