metadata
base_model: textattack/roberta-base-ag-news
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base-ag-news
results: []
roberta-base-ag-news
This model is a fine-tuned version of textattack/roberta-base-ag-news on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2200
- Accuracy: 0.9443
- F1: 0.9444
- Precision: 0.9444
- Recall: 0.9443
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.108 | 1.0 | 3750 | 0.2200 | 0.9443 | 0.9444 | 0.9444 | 0.9443 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1