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update model card README.md

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