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--- |
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license: mit |
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base_model: 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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model-index: |
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- name: roberta-large-depression-classification-v2 |
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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-large-depression-classification-v2 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2328 |
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- Accuracy: 0.5435 |
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- F1 Score: 0.5316 |
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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: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| 0.9778 | 1.0 | 677 | 1.2323 | 0.5380 | 0.5275 | |
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| 0.6377 | 2.0 | 1354 | 2.0223 | 0.5315 | 0.5125 | |
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| 0.5285 | 3.0 | 2031 | 2.2328 | 0.5435 | 0.5316 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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