metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-Dep
results: []
roberta-large-Dep
This model is a fine-tuned version of rafalposwiata/deproberta-large-depression on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8107
- Accuracy: 0.8517
- F1: 0.9118
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-06
- 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 |
|---|---|---|---|---|---|
| No log | 1.0 | 469 | 0.3701 | 0.87 | 0.9264 |
| 0.4293 | 2.0 | 938 | 0.4385 | 0.865 | 0.9219 |
| 0.3302 | 3.0 | 1407 | 0.5293 | 0.85 | 0.9109 |
| 0.2784 | 4.0 | 1876 | 0.7077 | 0.8517 | 0.9118 |
| 0.1914 | 5.0 | 2345 | 0.8107 | 0.8517 | 0.9118 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3