RajuEEE/RewardModel

README.md

@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6265
-- F1: 0.0207
-- Roc Auc: 0.5019
-- Accuracy: 0.0106
+- Loss: 0.6338
+- F1: 0.0
+- Roc Auc: 0.5
+- Accuracy: 0.0
 
 ## Model description
 
@@ -50,14 +50,14 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
-| No log        | 1.0   | 258  | 0.6265          | 0.0207 | 0.5019  | 0.0106   |
+| Training Loss | Epoch | Step | Validation Loss | F1  | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
+| No log        | 1.0   | 258  | 0.6338          | 0.0 | 0.5     | 0.0      |
 
 
 ### Framework versions
 
-- Transformers 4.32.0
+- Transformers 4.32.1
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.4
 - Tokenizers 0.13.3

config.json

@@ -30,7 +30,7 @@
   "position_embedding_type": "absolute",
   "problem_type": "multi_label_classification",
   "torch_dtype": "float32",
-  "transformers_version": "4.32.0",
+  "transformers_version": "4.32.1",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

pytorch_model.bin

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training_args.bin

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