metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: results
results: []
results
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0172
- eval_accuracy: 0.9968
- eval_precision: 0.9968
- eval_recall: 0.9968
- eval_f1: 0.9968
- eval_roc_auc: 0.9999
- eval_runtime: 273.0945
- eval_samples_per_second: 133.046
- eval_steps_per_second: 4.16
- epoch: 2.8622
- step: 13000
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.21.2