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---
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
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mental_roberta_stress
This model is a fine-tuned version of [mental/mental-roberta-base](https://huggingface.co/mental/mental-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4034
- Accuracy: 0.8266
- F1: 0.8278
- Precision: 0.8490
- Recall: 0.8076
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6934 | 0.99 | 31 | 0.6885 | 0.5427 | 0.6930 | 0.5302 | 1.0 |
| 0.6692 | 1.98 | 62 | 0.6606 | 0.5664 | 0.7042 | 0.5434 | 1.0 |
| 0.46 | 2.98 | 93 | 0.4357 | 0.8098 | 0.8116 | 0.8300 | 0.7940 |
| 0.3539 | 3.97 | 124 | 0.4034 | 0.8266 | 0.8278 | 0.8490 | 0.8076 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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