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almafaz
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roberta-depression-detection-hpc

Text Classification
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roberta
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End of training

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  1. README.md +19 -6
  2. logs/events.out.tfevents.1712122131.Nicolaj_PC.22664.3 +2 -2
  3. logs/events.out.tfevents.1712158060.Nicolaj_PC.22664.5 +3 -0
  4. pytorch_model.bin +1 -1
README.md CHANGED
@@ -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 [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6905
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  ## Model description
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@@ -34,20 +34,33 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 4e-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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  - 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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.6937 | 1.0 | 18 | 0.6927 |
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- | 0.6944 | 2.0 | 36 | 0.6905 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1689
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 4e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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  - lr_scheduler_warmup_steps: 500
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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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+ | 0.2808 | 1.0 | 215 | 0.1689 |
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+ | 0.144 | 2.0 | 430 | 0.2712 |
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+ | 0.0704 | 3.0 | 645 | 0.2503 |
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+ | 0.0791 | 4.0 | 860 | 0.2868 |
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+ | 0.0488 | 5.0 | 1075 | 0.2350 |
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+ | 0.061 | 6.0 | 1290 | 0.2155 |
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+ | 0.036 | 7.0 | 1505 | 0.2738 |
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+ | 0.0003 | 8.0 | 1720 | 0.2611 |
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+ | 0.0434 | 9.0 | 1935 | 0.2930 |
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+ | 0.0001 | 10.0 | 2150 | 0.2974 |
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+ | 0.0001 | 11.0 | 2365 | 0.3735 |
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+ | 0.0 | 12.0 | 2580 | 0.3582 |
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+ | 0.0 | 13.0 | 2795 | 0.3533 |
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+ | 0.0 | 14.0 | 3010 | 0.3443 |
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+ | 0.0 | 15.0 | 3225 | 0.3436 |
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  ### Framework versions
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