metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ami-command-recognition-sync-async-weighted
results: []
ami-command-recognition-sync-async-weighted
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0080
- Accuracy: 0.7578
- F1: 0.6533
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: 16
- eval_batch_size: 8
- 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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 41 | 1.0484 | 0.7578 | 0.6533 |
| No log | 2.0 | 82 | 1.0105 | 0.7640 | 0.6779 |
| No log | 3.0 | 123 | 1.0080 | 0.7578 | 0.6533 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu129
- Datasets 4.4.1
- Tokenizers 0.22.1