metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fm-tc-authenticv2
results: []
fm-tc-authenticv2
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4353
- Accuracy: 0.91
- Precision: 0.9121
- Recall: 0.9100
- F1: 0.9096
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.6462 | 1.0 | 500 | 0.6519 | 0.826 | 0.8439 | 0.8260 | 0.8181 |
| 0.5197 | 2.0 | 1000 | 0.4539 | 0.898 | 0.9012 | 0.8980 | 0.8970 |
| 0.3199 | 3.0 | 1500 | 0.4931 | 0.9 | 0.9067 | 0.9 | 0.9004 |
| 0.1987 | 4.0 | 2000 | 0.4353 | 0.91 | 0.9121 | 0.9100 | 0.9096 |
| 0.0944 | 5.0 | 2500 | 0.4598 | 0.92 | 0.9223 | 0.9200 | 0.9193 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1