metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-finetuned-depression
results: []
roberta-base-finetuned-depression
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6580
- Precision: 0.8962
- Recall: 0.9023
- F1: 0.8983
- Accuracy: 0.9062
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 469 | 0.4520 | 0.8637 | 0.7997 | 0.8216 | 0.8635 |
| 0.5796 | 2.0 | 938 | 0.6088 | 0.9063 | 0.8592 | 0.8733 | 0.8849 |
| 0.3217 | 3.0 | 1407 | 0.4402 | 0.8921 | 0.8964 | 0.8936 | 0.9030 |
| 0.2159 | 4.0 | 1876 | 0.6420 | 0.8725 | 0.8890 | 0.8789 | 0.8955 |
| 0.1496 | 5.0 | 2345 | 0.6017 | 0.8875 | 0.8973 | 0.8908 | 0.9019 |
| 0.0827 | 6.0 | 2814 | 0.6586 | 0.8804 | 0.9009 | 0.8895 | 0.9009 |
| 0.0504 | 7.0 | 3283 | 0.6580 | 0.8962 | 0.9023 | 0.8983 | 0.9062 |
| 0.05 | 8.0 | 3752 | 0.7374 | 0.8859 | 0.9013 | 0.8925 | 0.9030 |
| 0.0394 | 9.0 | 4221 | 0.7348 | 0.8746 | 0.9043 | 0.8880 | 0.9019 |
| 0.0241 | 10.0 | 4690 | 0.7371 | 0.8773 | 0.9027 | 0.8883 | 0.9030 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1