metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Openn_binary
results: []
Openn_binary
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6054
- Accuracy: 0.6847
- Precision: 0.6788
- Recall: 0.6417
- F1: 0.6597
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 130 | 0.6303 | 0.6403 | 0.7093 | 0.4150 | 0.5236 |
| No log | 2.0 | 260 | 0.6054 | 0.6847 | 0.6788 | 0.6417 | 0.6597 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1