metadata
license: mit
base_model: 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 roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2762
- Accuracy: 0.7751
- F1: 0.5205
- Precision: 0.5180
- Recall: 0.5235
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0829 | 1.0 | 612 | 1.0975 | 0.7771 | 0.6970 | 0.6937 | 0.7030 |
| 0.0937 | 2.0 | 1224 | 1.2088 | 0.7800 | 0.5233 | 0.5252 | 0.5219 |
| 0.0626 | 3.0 | 1836 | 1.2762 | 0.7751 | 0.5205 | 0.5180 | 0.5235 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1