Depression 3 classes
Browse files- README.md +70 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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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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- precision
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- recall
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- f1
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model-index:
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- name: mental-roberta_depression_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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# mental-roberta_depression_v2
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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: 0.5003
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- Accuracy: 0.7974
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- Precision: 0.7981
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- Recall: 0.7974
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- F1: 0.7972
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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: 24
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- eval_batch_size: 24
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_8BIT 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: 3
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- mixed_precision_training: Native AMP
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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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| 0.5859 | 1.0 | 969 | 0.5015 | 0.7693 | 0.7913 | 0.7693 | 0.7608 |
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| 0.416 | 2.0 | 1938 | 0.4553 | 0.7984 | 0.8032 | 0.7984 | 0.7980 |
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| 0.3386 | 3.0 | 2907 | 0.5003 | 0.7974 | 0.7981 | 0.7974 | 0.7972 |
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### Framework versions
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- Transformers 4.48.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 498615900
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version https://git-lfs.github.com/spec/v1
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size 498615900
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