metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: >-
roberta-Validation-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
results: []
roberta-Validation-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: 0.3698
- Accuracy: 0.8216
- Precision: 0.4348
- Recall: 0.5932
- F1: 0.5018
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: 1.6142257525574262e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4927 | 1.0 | 296 | 0.2877 | 0.8434 | 0.4792 | 0.3898 | 0.4299 |
| 0.3855 | 2.0 | 592 | 0.2566 | 0.8665 | 0.5714 | 0.4746 | 0.5185 |
| 0.3257 | 3.0 | 888 | 0.2534 | 0.8575 | 0.5368 | 0.4322 | 0.4789 |
| 0.2553 | 4.0 | 1184 | 0.3290 | 0.8216 | 0.4371 | 0.6186 | 0.5123 |
| 0.1911 | 5.0 | 1480 | 0.3698 | 0.8216 | 0.4348 | 0.5932 | 0.5018 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0