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_stress_classification
results: []
mental-roberta_stress_classification
This model is a fine-tuned version of mental/mental-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7029
- Accuracy: 0.5
- F1: 0.3333
- Precision: 0.25
- Recall: 0.5
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6983 | 1.0 | 48000 | 0.7029 | 0.5 | 0.3333 | 0.25 | 0.5 |
| 0.7189 | 2.0 | 96000 | 0.7414 | 0.5 | 0.3333 | 0.25 | 0.5 |
| 0.5927 | 3.0 | 144000 | 0.7370 | 0.5 | 0.3333 | 0.25 | 0.5 |
| 0.6274 | 4.0 | 192000 | 0.7668 | 0.5 | 0.3333 | 0.25 | 0.5 |
| 0.6622 | 5.0 | 240000 | 0.7478 | 0.5 | 0.3333 | 0.25 | 0.5 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2