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Bert_uncased_fine_tuned_Reward_Model

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - poem_sentiment
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: Bert_uncased_fine_tuned_Reward_Model
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: poem_sentiment
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+ type: poem_sentiment
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.875
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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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+ # Bert_uncased_fine_tuned_Reward_Model
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the poem_sentiment dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0876
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+ - Mse: 0.0876
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+ - Mae: 0.1403
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+ - R2: 0.7389
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+ - Accuracy: 0.875
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 53 | 0.1744 | 0.1744 | 0.2973 | 0.4805 | 0.7885 |
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+ | No log | 2.0 | 106 | 0.1074 | 0.1074 | 0.2333 | 0.6801 | 0.8846 |
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+ | No log | 3.0 | 159 | 0.1026 | 0.1026 | 0.2134 | 0.6943 | 0.8654 |
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+ | No log | 4.0 | 212 | 0.0877 | 0.0877 | 0.1841 | 0.7388 | 0.8942 |
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+ | No log | 5.0 | 265 | 0.1000 | 0.1000 | 0.2007 | 0.7021 | 0.8942 |
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+ | No log | 6.0 | 318 | 0.0863 | 0.0863 | 0.1738 | 0.7429 | 0.8942 |
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+ | No log | 7.0 | 371 | 0.0966 | 0.0966 | 0.1827 | 0.7122 | 0.8846 |
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+ | No log | 8.0 | 424 | 0.0946 | 0.0946 | 0.1701 | 0.7183 | 0.8846 |
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+ | No log | 9.0 | 477 | 0.0978 | 0.0978 | 0.1658 | 0.7088 | 0.875 |
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+ | 0.0516 | 10.0 | 530 | 0.0854 | 0.0854 | 0.1639 | 0.7457 | 0.875 |
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+ | 0.0516 | 11.0 | 583 | 0.0947 | 0.0947 | 0.1620 | 0.7181 | 0.8846 |
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+ | 0.0516 | 12.0 | 636 | 0.0907 | 0.0907 | 0.1516 | 0.7297 | 0.8846 |
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+ | 0.0516 | 13.0 | 689 | 0.0885 | 0.0885 | 0.1546 | 0.7364 | 0.875 |
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+ | 0.0516 | 14.0 | 742 | 0.0849 | 0.0849 | 0.1452 | 0.7471 | 0.8942 |
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+ | 0.0516 | 15.0 | 795 | 0.0823 | 0.0823 | 0.1428 | 0.7548 | 0.8846 |
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+ | 0.0516 | 16.0 | 848 | 0.0864 | 0.0864 | 0.1429 | 0.7427 | 0.8846 |
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+ | 0.0516 | 17.0 | 901 | 0.0854 | 0.0854 | 0.1427 | 0.7457 | 0.8846 |
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+ | 0.0516 | 18.0 | 954 | 0.0860 | 0.0860 | 0.1429 | 0.7437 | 0.875 |
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+ | 0.0059 | 19.0 | 1007 | 0.0871 | 0.0871 | 0.1438 | 0.7406 | 0.875 |
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+ | 0.0059 | 20.0 | 1060 | 0.0876 | 0.0876 | 0.1403 | 0.7389 | 0.875 |
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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 1.13.1+cu116
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2