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End of training

Browse files
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7029
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- - Accuracy: 0.5
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- - F1: 0.3333
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- - Precision: 0.25
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- - Recall: 0.5
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  ## Model description
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@@ -50,22 +50,19 @@ 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: 5
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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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- | 0.6983 | 1.0 | 48000 | 0.7029 | 0.5 | 0.3333 | 0.25 | 0.5 |
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- | 0.7189 | 2.0 | 96000 | 0.7414 | 0.5 | 0.3333 | 0.25 | 0.5 |
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- | 0.5927 | 3.0 | 144000 | 0.7370 | 0.5 | 0.3333 | 0.25 | 0.5 |
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- | 0.6274 | 4.0 | 192000 | 0.7668 | 0.5 | 0.3333 | 0.25 | 0.5 |
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- | 0.6622 | 5.0 | 240000 | 0.7478 | 0.5 | 0.3333 | 0.25 | 0.5 |
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  ### Framework versions
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- - Transformers 4.32.1
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.12.0
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- - Tokenizers 0.13.2
 
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  This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0096
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+ - Accuracy: 0.9984
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+ - F1: 0.9984
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+ - Precision: 0.9984
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+ - Recall: 0.9984
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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: 2
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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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+ | 0.0006 | 1.0 | 8000 | 0.0239 | 0.9966 | 0.9966 | 0.9966 | 0.9966 |
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+ | 0.0002 | 2.0 | 16000 | 0.0096 | 0.9984 | 0.9984 | 0.9984 | 0.9984 |
 
 
 
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  ### Framework versions
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+ - Transformers 4.38.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.14.7
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+ - Tokenizers 0.15.2
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