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--- |
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license: cc-by-nc-4.0 |
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base_model: mental/mental-roberta-base |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: mental-roberta-base-CD_baseline |
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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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# mental-roberta-base-CD_baseline |
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This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2770 |
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- Accuracy: 0.5957 |
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- F1: 0.5795 |
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- Precision: 0.5801 |
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- Recall: 0.5957 |
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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: 2e-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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- 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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.7629 | 1.0 | 250 | 1.5328 | 0.4739 | 0.3843 | 0.3535 | 0.4739 | |
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| 1.4033 | 2.0 | 500 | 1.3282 | 0.5261 | 0.5010 | 0.5395 | 0.5261 | |
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| 0.7635 | 3.0 | 750 | 1.3102 | 0.5609 | 0.5337 | 0.5372 | 0.5609 | |
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| 0.8688 | 4.0 | 1000 | 1.2770 | 0.5957 | 0.5795 | 0.5801 | 0.5957 | |
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| 0.4432 | 5.0 | 1250 | 1.4374 | 0.6087 | 0.5941 | 0.6038 | 0.6087 | |
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| 0.3489 | 6.0 | 1500 | 1.4813 | 0.5870 | 0.5901 | 0.6124 | 0.5870 | |
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| 0.3154 | 7.0 | 1750 | 1.5613 | 0.5913 | 0.5923 | 0.6051 | 0.5913 | |
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| 0.1553 | 8.0 | 2000 | 1.6126 | 0.5957 | 0.5931 | 0.5986 | 0.5957 | |
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### Framework versions |
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- Transformers 4.38.0 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.2.0 |
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- Tokenizers 0.15.2 |
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