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MTL-bert-base-uncased

Fill-Mask Transformers PyTorch TensorBoard bert generated_from_trainer Inference Endpoints
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update model card README.md

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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2486
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  ## Model description
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@@ -34,32 +34,33 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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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  - num_epochs: 15
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 94 | 2.6014 |
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- | No log | 2.0 | 188 | 2.3898 |
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- | No log | 3.0 | 282 | 2.3706 |
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- | No log | 4.0 | 376 | 2.2708 |
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- | No log | 5.0 | 470 | 2.2666 |
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- | 2.5403 | 6.0 | 564 | 2.2639 |
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- | 2.5403 | 7.0 | 658 | 2.3061 |
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- | 2.5403 | 8.0 | 752 | 2.2659 |
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- | 2.5403 | 9.0 | 846 | 2.1882 |
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- | 2.5403 | 10.0 | 940 | 2.2198 |
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- | 2.2739 | 11.0 | 1034 | 2.1124 |
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- | 2.2739 | 12.0 | 1128 | 2.1887 |
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- | 2.2739 | 13.0 | 1222 | 2.1740 |
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- | 2.2739 | 14.0 | 1316 | 2.1517 |
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- | 2.2739 | 15.0 | 1410 | 2.1510 |
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  ### Framework versions
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9283
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 7
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+ - eval_batch_size: 7
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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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  - num_epochs: 15
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.4409 | 1.0 | 99 | 2.1982 |
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+ | 2.2905 | 2.0 | 198 | 2.1643 |
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+ | 2.1974 | 3.0 | 297 | 2.1168 |
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+ | 2.15 | 4.0 | 396 | 2.0023 |
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+ | 2.0823 | 5.0 | 495 | 2.0199 |
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+ | 2.0752 | 6.0 | 594 | 1.9061 |
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+ | 2.0408 | 7.0 | 693 | 1.9770 |
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+ | 1.9984 | 8.0 | 792 | 1.9322 |
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+ | 1.9933 | 9.0 | 891 | 1.9167 |
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+ | 1.9806 | 10.0 | 990 | 1.9652 |
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+ | 1.9436 | 11.0 | 1089 | 1.9308 |
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+ | 1.9491 | 12.0 | 1188 | 1.9064 |
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+ | 1.929 | 13.0 | 1287 | 1.8831 |
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+ | 1.9096 | 14.0 | 1386 | 1.8927 |
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+ | 1.9032 | 15.0 | 1485 | 1.9117 |
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  ### Framework versions