metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Mixed-replace-vi
results: []
xlm-roberta-base-Mixed-replace-vi
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6016
- Accuracy: 0.8018
- F1: 0.7987
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | F1 |
|---|---|---|---|---|---|
| 0.1619 | 1.0 | 294 | 1.2621 | 0.7882 | 0.7966 |
| 0.1296 | 2.0 | 588 | 1.3555 | 0.7973 | 0.8000 |
| 0.1191 | 3.0 | 882 | 1.4282 | 0.7837 | 0.7902 |
| 0.0991 | 4.0 | 1176 | 1.3073 | 0.7958 | 0.7980 |
| 0.0478 | 5.0 | 1470 | 1.5468 | 0.7988 | 0.7996 |
| 0.0527 | 6.0 | 1764 | 1.4876 | 0.7988 | 0.8033 |
| 0.0528 | 7.0 | 2058 | 1.4934 | 0.8064 | 0.8012 |
| 0.0474 | 8.0 | 2352 | 1.5715 | 0.8079 | 0.8047 |
| 0.04 | 9.0 | 2646 | 1.5777 | 0.8033 | 0.7978 |
| 0.0266 | 10.0 | 2940 | 1.6016 | 0.8018 | 0.7987 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3