metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: train
results: []
train
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0145
- Accuracy: 0.9966
- F1: 0.9966
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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2363 | 1.0 | 1422 | 0.0150 | 0.9963 | 0.9963 |
| 0.0116 | 2.0 | 2844 | 0.0145 | 0.9966 | 0.9966 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.11.0
- Datasets 2.12.0
- Tokenizers 0.13.3