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mhr2004
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plm-nsp-1000

Text Classification
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roberta
Generated from Trainer
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mhr2004/plm-nsp-1000

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  1. README.md +10 -21
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3707
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  ## Model description
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@@ -35,8 +35,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 1024
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- - eval_batch_size: 1024
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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
@@ -46,24 +46,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6954 | 1.0 | 2 | 0.6917 |
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- | 0.6912 | 2.0 | 4 | 0.6874 |
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- | 0.6877 | 3.0 | 6 | 0.6784 |
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- | 0.6744 | 4.0 | 8 | 0.6388 |
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- | 0.6384 | 5.0 | 10 | 0.5990 |
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- | 0.5988 | 6.0 | 12 | 0.4962 |
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- | 0.5429 | 7.0 | 14 | 0.4770 |
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- | 0.4862 | 8.0 | 16 | 0.4000 |
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- | 0.4598 | 9.0 | 18 | 0.3830 |
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- | 0.3835 | 10.0 | 20 | 0.4515 |
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- | 0.3459 | 11.0 | 22 | 0.3672 |
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- | 0.3335 | 12.0 | 24 | 0.3659 |
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- | 0.2611 | 13.0 | 26 | 0.3834 |
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- | 0.2407 | 14.0 | 28 | 0.3613 |
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- | 0.2018 | 15.0 | 30 | 0.3567 |
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- | 0.1758 | 16.0 | 32 | 0.3612 |
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- | 0.152 | 17.0 | 34 | 0.3645 |
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- | 0.1408 | 18.0 | 36 | 0.3707 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5632
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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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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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6837 | 1.0 | 16 | 0.6045 |
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+ | 0.531 | 2.0 | 32 | 0.3439 |
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+ | 0.2985 | 3.0 | 48 | 0.3287 |
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+ | 0.1592 | 4.0 | 64 | 0.3131 |
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+ | 0.1162 | 5.0 | 80 | 0.3560 |
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+ | 0.0749 | 6.0 | 96 | 0.4225 |
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+ | 0.0636 | 7.0 | 112 | 0.5632 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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