metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Questions-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
results: []
roberta-Questions-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3192
- Accuracy: 0.7805
- Precision: 0.6813
- Recall: 0.8185
- F1: 0.7436
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: 3.0384066791847988e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5249 | 1.0 | 165 | 0.2628 | 0.6110 | 0.0 | 0.0 | 0.0 |
| 0.4371 | 2.0 | 330 | 0.3133 | 0.7843 | 0.6517 | 0.9571 | 0.7754 |
| 0.3969 | 3.0 | 495 | 0.2745 | 0.6226 | 0.6364 | 0.0693 | 0.125 |
| 0.3765 | 4.0 | 660 | 0.3192 | 0.7805 | 0.6813 | 0.8185 | 0.7436 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0