metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: mental/mental-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mental-roberta_depression_v2
results: []
mental-roberta_depression_v2
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: 0.5003
- Accuracy: 0.7974
- Precision: 0.7981
- Recall: 0.7974
- F1: 0.7972
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: 2e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5859 | 1.0 | 969 | 0.5015 | 0.7693 | 0.7913 | 0.7693 | 0.7608 |
| 0.416 | 2.0 | 1938 | 0.4553 | 0.7984 | 0.8032 | 0.7984 | 0.7980 |
| 0.3386 | 3.0 | 2907 | 0.5003 | 0.7974 | 0.7981 | 0.7974 | 0.7972 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0