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End of training

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  1. README.md +22 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -4,6 +4,9 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
 
 
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  model-index:
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  - name: nb-bert-base-user-needs
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  results: []
@@ -16,8 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7182
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- - Accuracy: 0.7985
 
 
 
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  ## Model description
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@@ -43,21 +49,28 @@ The following hyperparameters were used during training:
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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_steps: 500
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- - num_epochs: 3
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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 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 97 | 1.0333 | 0.6633 |
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- | No log | 2.0 | 194 | 0.8062 | 0.7832 |
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- | No log | 3.0 | 291 | 0.7182 | 0.7985 |
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.17.0
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  - Pytorch 1.10.2+cu113
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- - Datasets 1.18.4
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  - Tokenizers 0.12.1
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: nb-bert-base-user-needs
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  results: []
 
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  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6468
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+ - Accuracy: 0.8582
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+ - F1: 0.8388
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+ - Precision: 0.8295
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+ - Recall: 0.8582
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  ## Model description
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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_steps: 500
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+ - num_epochs: 10
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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 | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 98 | 1.2122 | 0.6005 | 0.4506 | 0.3606 | 0.6005 |
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+ | No log | 2.0 | 196 | 0.9735 | 0.7113 | 0.6231 | 0.5549 | 0.7113 |
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+ | No log | 3.0 | 294 | 0.7894 | 0.7655 | 0.6996 | 0.7399 | 0.7655 |
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+ | No log | 4.0 | 392 | 0.9499 | 0.6933 | 0.6584 | 0.6617 | 0.6933 |
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+ | No log | 5.0 | 490 | 0.7529 | 0.7784 | 0.7217 | 0.7107 | 0.7784 |
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+ | 0.9006 | 6.0 | 588 | 0.7510 | 0.7964 | 0.7491 | 0.7370 | 0.7964 |
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+ | 0.9006 | 7.0 | 686 | 0.5963 | 0.8273 | 0.8044 | 0.7960 | 0.8273 |
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+ | 0.9006 | 8.0 | 784 | 0.6918 | 0.8351 | 0.8071 | 0.8096 | 0.8351 |
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+ | 0.9006 | 9.0 | 882 | 0.7391 | 0.8273 | 0.8017 | 0.8042 | 0.8273 |
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+ | 0.9006 | 10.0 | 980 | 0.6468 | 0.8582 | 0.8388 | 0.8295 | 0.8582 |
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  ### Framework versions
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  - Transformers 4.17.0
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  - Pytorch 1.10.2+cu113
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+ - Datasets 2.3.2
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  - Tokenizers 0.12.1
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