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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-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current |
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results: [] |
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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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# roberta-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current |
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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: 0.0525 |
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- Accuracy: 0.9820 |
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- Precision: 0.7838 |
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- Recall: 0.8286 |
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- F1: 0.8056 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1.5021066734744005e-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: 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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.3227 | 1.0 | 109 | 0.0632 | 0.9551 | 0.0 | 0.0 | 0.0 | |
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| 0.1297 | 2.0 | 218 | 0.0649 | 0.9782 | 0.7045 | 0.8857 | 0.7848 | |
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| 0.1211 | 3.0 | 327 | 0.0409 | 0.9692 | 0.6 | 0.9429 | 0.7333 | |
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| 0.1021 | 4.0 | 436 | 0.0599 | 0.9730 | 0.64 | 0.9143 | 0.7529 | |
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| 0.0797 | 5.0 | 545 | 0.0907 | 0.9756 | 0.66 | 0.9429 | 0.7765 | |
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| 0.0746 | 6.0 | 654 | 0.1045 | 0.9730 | 0.6346 | 0.9429 | 0.7586 | |
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| 0.0607 | 7.0 | 763 | 0.0720 | 0.9820 | 0.7333 | 0.9429 | 0.825 | |
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| 0.0419 | 8.0 | 872 | 0.0771 | 0.9782 | 0.7045 | 0.8857 | 0.7848 | |
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| 0.0632 | 9.0 | 981 | 0.0536 | 0.9846 | 0.7949 | 0.8857 | 0.8378 | |
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| 0.0456 | 10.0 | 1090 | 0.0525 | 0.9820 | 0.7838 | 0.8286 | 0.8056 | |
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### Framework versions |
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- Transformers 4.49.0 |
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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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