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: results
results: []
results
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: 0.7715
- Accuracy: 0.8014
- F1: 0.8161
- Precision: 0.7816
- Recall: 0.8537
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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3921 | 0.99 | 31 | 0.4379 | 0.8042 | 0.8153 | 0.7943 | 0.8374 |
| 0.3376 | 1.98 | 62 | 0.4358 | 0.8112 | 0.8173 | 0.8162 | 0.8184 |
| 0.3126 | 2.98 | 93 | 0.4642 | 0.7972 | 0.8172 | 0.7642 | 0.8780 |
| 0.2838 | 4.0 | 125 | 0.4438 | 0.8196 | 0.8264 | 0.8209 | 0.8320 |
| 0.2504 | 4.99 | 156 | 0.5249 | 0.7958 | 0.8161 | 0.7624 | 0.8780 |
| 0.2912 | 5.98 | 187 | 0.6067 | 0.7972 | 0.8221 | 0.7511 | 0.9079 |
| 0.1335 | 6.98 | 218 | 0.7014 | 0.8 | 0.8197 | 0.7665 | 0.8808 |
| 0.1579 | 7.94 | 248 | 0.7715 | 0.8014 | 0.8161 | 0.7816 | 0.8537 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2