metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: baseline_roberta-large_epoch3_batch4_lr2e-05_w0.01
results: []
baseline_roberta-large_epoch3_batch4_lr2e-05_w0.01
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5836
- Accuracy: 0.7164
- F1: 0.3943
- Precision: 0.9651
- Recall: 0.2478
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 0.7073 | 1.0 | 788 | 0.6524 | 0.6274 | 0.0 | 0.0 | 0.0 |
| 0.668 | 2.0 | 1576 | 0.5835 | 0.6274 | 0.0 | 0.0 | 0.0 |
| 0.6148 | 3.0 | 2364 | 0.5836 | 0.7164 | 0.3943 | 0.9651 | 0.2478 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3