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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: FacebookAI/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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+ model-index:
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+ - name: roberta_base_classification_model_depression_detection
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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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+ # roberta_base_classification_model_depression_detection
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0822
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+ - Accuracy: 0.9819
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+ - F1 Score: 0.9828
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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: 3e-05
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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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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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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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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 4
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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 | F1 Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | No log | 1.0 | 386 | 0.0517 | 0.9767 | 0.9776 |
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+ | 0.1806 | 2.0 | 773 | 0.0383 | 0.9871 | 0.9878 |
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+ | 0.0668 | 3.0 | 1159 | 0.0614 | 0.9845 | 0.9851 |
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+ | 0.0294 | 3.99 | 1544 | 0.0822 | 0.9819 | 0.9828 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.15.2
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+ ],
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+ "model_type": "roberta",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ }
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