update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: gptneo-1.3B-rm-harmless
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# gptneo-1.3B-rm-harmless
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5449
+- Accuracy: 0.7184
+- Average Pos Score: 1.1621
+- Average Neg Score: 0.4114
+- Average Abs Score Diff: 1.1133
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Average Pos Score | Average Neg Score | Average Abs Score Diff |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:-----------------:|:----------------------:|
+| 0.6274        | 0.15  | 200  | 0.5898          | 0.6968   | 1.7881            | 1.2979            | 0.8413                 |
+| 0.5058        | 0.3   | 400  | 0.5811          | 0.7115   | 0.8394            | -0.0314           | 1.3799                 |
+| 0.5699        | 0.45  | 600  | 0.5527          | 0.7167   | 1.2803            | 0.6006            | 1.0293                 |
+| 0.5533        | 0.6   | 800  | 0.5542          | 0.7171   | 0.6689            | -0.1876           | 1.2930                 |
+| 0.5396        | 0.75  | 1000 | 0.5444          | 0.7223   | 1.0977            | 0.3601            | 1.0977                 |
+| 0.5791        | 0.9   | 1200 | 0.5449          | 0.7184   | 1.1621            | 0.4114            | 1.1133                 |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.9.0
+- Tokenizers 0.13.2