metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: classifier_roberta
results: []
classifier_roberta
This model is a fine-tuned version of FacebookAI/roberta-large-mnli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6933
- Accuracy: 0.4392
- Precision: 0.4392
- Recall: 1.0
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- num_epochs: 32
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| No log | 1.0 | 358 | 0.8518 | 0.4392 | 0.4392 | 1.0 |
| 0.7654 | 2.0 | 716 | 0.7826 | 0.4392 | 0.4392 | 1.0 |
| 0.7448 | 3.0 | 1074 | 0.8327 | 0.4392 | 0.4392 | 1.0 |
| 0.7448 | 4.0 | 1432 | 0.7101 | 0.5608 | 0.0 | 0.0 |
| 0.7469 | 5.0 | 1790 | 0.6857 | 0.5608 | 0.0 | 0.0 |
| 0.758 | 6.0 | 2148 | 0.6858 | 0.5608 | 0.0 | 0.0 |
| 0.7646 | 7.0 | 2506 | 0.7054 | 0.4392 | 0.4392 | 1.0 |
| 0.7646 | 8.0 | 2864 | 0.7196 | 0.4392 | 0.4392 | 1.0 |
| 0.7329 | 9.0 | 3222 | 0.6947 | 0.4392 | 0.4392 | 1.0 |
| 0.747 | 10.0 | 3580 | 0.7143 | 0.4392 | 0.4392 | 1.0 |
| 0.747 | 11.0 | 3938 | 0.6863 | 0.5608 | 0.0 | 0.0 |
| 0.7343 | 12.0 | 4296 | 0.6857 | 0.5608 | 0.0 | 0.0 |
| 0.7461 | 13.0 | 4654 | 0.7057 | 0.4392 | 0.4392 | 1.0 |
| 0.7279 | 14.0 | 5012 | 0.6893 | 0.5608 | 0.0 | 0.0 |
| 0.7279 | 15.0 | 5370 | 0.7015 | 0.4392 | 0.4392 | 1.0 |
| 0.735 | 16.0 | 5728 | 0.7138 | 0.4392 | 0.4392 | 1.0 |
| 0.73 | 17.0 | 6086 | 0.7042 | 0.5608 | 0.0 | 0.0 |
| 0.73 | 18.0 | 6444 | 0.7084 | 0.4392 | 0.4392 | 1.0 |
| 0.7299 | 19.0 | 6802 | 0.6978 | 0.4392 | 0.4392 | 1.0 |
| 0.7216 | 20.0 | 7160 | 0.6924 | 0.5608 | 0.0 | 0.0 |
| 0.7246 | 21.0 | 7518 | 0.7701 | 0.4392 | 0.4392 | 1.0 |
| 0.7246 | 22.0 | 7876 | 0.9114 | 0.4392 | 0.4392 | 1.0 |
| 0.7183 | 23.0 | 8234 | 0.8309 | 0.4392 | 0.4392 | 1.0 |
| 0.7158 | 24.0 | 8592 | 0.6875 | 0.5608 | 0.0 | 0.0 |
| 0.7158 | 25.0 | 8950 | 0.6875 | 0.5608 | 0.0 | 0.0 |
| 0.7112 | 26.0 | 9308 | 0.6857 | 0.5608 | 0.0 | 0.0 |
| 0.7097 | 27.0 | 9666 | 0.6913 | 0.5608 | 0.0 | 0.0 |
| 0.7076 | 28.0 | 10024 | 0.6996 | 0.4392 | 0.4392 | 1.0 |
| 0.7076 | 29.0 | 10382 | 0.7932 | 0.4392 | 0.4392 | 1.0 |
| 0.704 | 30.0 | 10740 | 0.6858 | 0.5608 | 0.0 | 0.0 |
| 0.7007 | 31.0 | 11098 | 0.6975 | 0.4392 | 0.4392 | 1.0 |
| 0.7007 | 32.0 | 11456 | 0.6933 | 0.4392 | 0.4392 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1