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Depression

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  2. adapter_model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: peft
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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
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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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+ # mental-roberta_depression
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+
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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: 0.3758
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+ - Accuracy: 0.8338
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+ - Precision: 0.8201
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+ - Recall: 0.8338
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+ - F1: 0.8243
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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: 2e-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_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: 5
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+ - mixed_precision_training: Native AMP
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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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+ | No log | 1.0 | 178 | 0.4578 | 0.8085 | 0.6536 | 0.8085 | 0.7228 |
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+ | No log | 2.0 | 356 | 0.3903 | 0.8366 | 0.8167 | 0.8366 | 0.8100 |
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+ | 0.495 | 3.0 | 534 | 0.3784 | 0.8338 | 0.8123 | 0.8338 | 0.8098 |
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+ | 0.495 | 4.0 | 712 | 0.3753 | 0.8366 | 0.8204 | 0.8366 | 0.8239 |
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+ | 0.495 | 5.0 | 890 | 0.3758 | 0.8338 | 0.8201 | 0.8338 | 0.8243 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.0
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+ - Tokenizers 0.21.0
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