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RajuEEE/RewardModel_RobertaBase

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: RewardModel_RobertaBase
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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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+ # RewardModel_RobertaBase
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5009
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+ - F1: 0.7738
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+ - Roc Auc: 0.7738
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+ - Accuracy: 0.7698
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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+
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+ ### Training results
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+
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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 | 93 | 0.5440 | 0.7331 | 0.7341 | 0.7302 |
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+ | 0.648 | 2.0 | 186 | 0.5009 | 0.7738 | 0.7738 | 0.7698 |
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+ | 0.5515 | 3.0 | 279 | 0.4938 | 0.7545 | 0.7560 | 0.75 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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+ "RobertaForSequenceClassification"
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+ ],
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+ "layer_norm_eps": 1e-05,
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "multi_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ }
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