metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fm-tc-end_mix_xml
results: []
fm-tc-end_mix_xml
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: 0.2061
- Accuracy: 0.97
- Precision: 0.9706
- Recall: 0.9700
- F1: 0.9700
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.6642 | 1.0 | 1188 | 0.4540 | 0.894 | 0.8983 | 0.8940 | 0.8938 |
0.4074 | 2.0 | 2376 | 0.4206 | 0.918 | 0.9241 | 0.9180 | 0.9183 |
0.2403 | 3.0 | 3564 | 0.4380 | 0.918 | 0.9221 | 0.9180 | 0.9165 |
0.1625 | 4.0 | 4752 | 0.4773 | 0.926 | 0.9297 | 0.9260 | 0.9262 |
0.0991 | 5.0 | 5940 | 0.2999 | 0.952 | 0.9536 | 0.9520 | 0.9521 |
0.0549 | 6.0 | 7128 | 0.2217 | 0.966 | 0.9671 | 0.966 | 0.9659 |
0.0226 | 7.0 | 8316 | 0.2770 | 0.964 | 0.9650 | 0.9640 | 0.9637 |
0.0154 | 8.0 | 9504 | 0.2061 | 0.97 | 0.9706 | 0.9700 | 0.9700 |
0.0061 | 9.0 | 10692 | 0.2372 | 0.97 | 0.9706 | 0.9700 | 0.9699 |
0.0048 | 10.0 | 11880 | 0.2419 | 0.964 | 0.9650 | 0.9640 | 0.9640 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1