metadata
license: cc-by-nc-4.0
base_model: mental/mental-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: mental_roberta_depression
results: []
mental_roberta_depression
This model is a fine-tuned version of mental/mental-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3151
- Accuracy: 0.8698
- F1: 0.9191
- Precision: 0.8785
- Recall: 0.9636
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4479 | 0.96 | 15 | 0.4467 | 0.7674 | 0.8684 | 0.7674 | 1.0 |
| 0.4121 | 1.98 | 31 | 0.4025 | 0.7674 | 0.8684 | 0.7674 | 1.0 |
| 0.3394 | 3.0 | 47 | 0.3229 | 0.7674 | 0.8684 | 0.7674 | 1.0 |
| 0.2806 | 3.82 | 60 | 0.3151 | 0.8698 | 0.9191 | 0.8785 | 0.9636 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2