SudhaBhattacharjee commited on
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SudhaBhattacharjee/Classifier3_e5-small-v2

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README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  library_name: transformers
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  license: mit
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- base_model: microsoft/deberta-v3-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # RewardModel_deberta-v3-large
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- This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1138
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  - Accuracy: 1.0
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  - F1: 1.0
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  - Roc Auc: 1.0
@@ -54,11 +54,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Roc Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|
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- | No log | 1.0 | 20 | 0.6241 | 0.98 | 0.9800 | 0.98 |
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- | No log | 2.0 | 40 | 0.1138 | 1.0 | 1.0 | 1.0 |
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- | No log | 3.0 | 60 | 0.0122 | 1.0 | 1.0 | 1.0 |
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- | No log | 4.0 | 80 | 0.0050 | 1.0 | 1.0 | 1.0 |
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- | 0.2382 | 5.0 | 100 | 0.0040 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: mit
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+ base_model: intfloat/e5-small-v2
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # RewardModel_deberta-v3-large
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+ This model is a fine-tuned version of [intfloat/e5-small-v2](https://huggingface.co/intfloat/e5-small-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5170
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  - Accuracy: 1.0
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  - F1: 1.0
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  - Roc Auc: 1.0
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Roc Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|
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+ | No log | 1.0 | 20 | 0.6583 | 0.56 | 0.4544 | 0.56 |
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+ | No log | 2.0 | 40 | 0.5170 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 60 | 0.3450 | 1.0 | 1.0 | 1.0 |
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+ | No log | 4.0 | 80 | 0.2474 | 1.0 | 1.0 | 1.0 |
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+ | 0.4644 | 5.0 | 100 | 0.2256 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
config.json CHANGED
@@ -1,44 +1,33 @@
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- "DebertaV2ForSequenceClassification"
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  ],
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  }
 
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  "problem_type": "single_label_classification",
 
 
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