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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/roberta-large
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: roberta-Reflections-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
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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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+ # roberta-Reflections-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1943
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+ - Accuracy: 0.8614
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+ - Precision: 0.4118
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+ - Recall: 0.5632
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+ - F1: 0.4757
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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: 5.754545003620396e-06
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.3812 | 1.0 | 52 | 0.1339 | 0.8883 | 0.0 | 0.0 | 0.0 |
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+ | 0.3106 | 2.0 | 104 | 0.1749 | 0.8883 | 0.0 | 0.0 | 0.0 |
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+ | 0.271 | 3.0 | 156 | 0.1669 | 0.8896 | 0.5098 | 0.2989 | 0.3768 |
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+ | 0.2632 | 4.0 | 208 | 0.2907 | 0.8742 | 0.4466 | 0.5287 | 0.4842 |
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+ | 0.2633 | 5.0 | 260 | 0.1745 | 0.9063 | 0.7917 | 0.2184 | 0.3423 |
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+ | 0.2377 | 6.0 | 312 | 0.1395 | 0.9050 | 0.6444 | 0.3333 | 0.4394 |
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+ | 0.2313 | 7.0 | 364 | 0.1491 | 0.8973 | 0.5522 | 0.4253 | 0.4805 |
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+ | 0.2159 | 8.0 | 416 | 0.2275 | 0.8498 | 0.3913 | 0.6207 | 0.48 |
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+ | 0.2159 | 9.0 | 468 | 0.1175 | 0.9076 | 0.6190 | 0.4483 | 0.52 |
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+ | 0.2007 | 10.0 | 520 | 0.1754 | 0.8768 | 0.4587 | 0.5747 | 0.5102 |
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+ | 0.1852 | 11.0 | 572 | 0.1671 | 0.8806 | 0.4688 | 0.5172 | 0.4918 |
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+ | 0.1874 | 12.0 | 624 | 0.1427 | 0.8947 | 0.5316 | 0.4828 | 0.5060 |
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+ | 0.175 | 13.0 | 676 | 0.1689 | 0.8716 | 0.4316 | 0.4713 | 0.4505 |
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+ | 0.1583 | 14.0 | 728 | 0.2238 | 0.8331 | 0.3576 | 0.6207 | 0.4538 |
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+ | 0.1708 | 15.0 | 780 | 0.1513 | 0.8793 | 0.4624 | 0.4943 | 0.4778 |
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+ | 0.1464 | 16.0 | 832 | 0.2165 | 0.8498 | 0.3881 | 0.5977 | 0.4706 |
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+ | 0.1473 | 17.0 | 884 | 0.2360 | 0.8357 | 0.3605 | 0.6092 | 0.4530 |
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+ | 0.1448 | 18.0 | 936 | 0.2004 | 0.8601 | 0.4083 | 0.5632 | 0.4734 |
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+ | 0.1437 | 19.0 | 988 | 0.1945 | 0.8601 | 0.4083 | 0.5632 | 0.4734 |
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+ | 0.1359 | 20.0 | 1040 | 0.1943 | 0.8614 | 0.4118 | 0.5632 | 0.4757 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 2.21.0
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+ - Tokenizers 0.21.0
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