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RajuEEE
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RewardModel

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
text-embeddings-inference
Model card Files
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 Community
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RajuEEE commited on
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RajuEEE/RewardModel

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Files changed (4) hide show
  1. README.md +8 -10
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +16 -2
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,10 +18,10 @@ 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: 0.6302
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- - F1: 0.0569
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- - Roc Auc: 0.5088
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- - Accuracy: 0.03
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  ## Model description
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@@ -46,15 +46,13 @@ The following hyperparameters were used during training:
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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: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 258 | 0.6355 | 0.0 | 0.5 | 0.0 |
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- | 0.6342 | 2.0 | 516 | 0.6364 | 0.0472 | 0.5038 | 0.025 |
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- | 0.6342 | 3.0 | 774 | 0.6302 | 0.0569 | 0.5088 | 0.03 |
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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: 0.6180
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+ - F1: 0.0
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+ - Roc Auc: 0.5
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+ - Accuracy: 0.0
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  ## Model description
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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: 1
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
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+ | No log | 1.0 | 258 | 0.6180 | 0.0 | 0.5 | 0.0 |
 
 
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  ### Framework versions
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