metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: roberta-rmi
results: []
roberta-rmi
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4169
- Accuracy: 0.8724
- Recall: 0.8634
- Precision: 0.8637
- F1: 0.8634
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 0.4904 | 1.0 | 2633 | 0.4169 | 0.8650 | 0.8547 | 0.8611 | 0.8562 |
| 0.3694 | 2.0 | 5266 | 0.4061 | 0.8708 | 0.8636 | 0.8626 | 0.8619 |
| 0.3018 | 3.0 | 7899 | 0.4169 | 0.8724 | 0.8634 | 0.8637 | 0.8634 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2