metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_xlm_r_only_bg
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: bg
split: train
args: bg
metrics:
- name: Accuracy
type: accuracy
value: 0.7839357429718875
xnli_xlm_r_only_bg
This model is a fine-tuned version of xlm-roberta-base on the xnli dataset. It achieves the following results on the evaluation set:
- Loss: 0.7896
- Accuracy: 0.7839
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6649 | 1.0 | 3068 | 0.5678 | 0.7659 |
| 0.5321 | 2.0 | 6136 | 0.5338 | 0.7932 |
| 0.4668 | 3.0 | 9204 | 0.5648 | 0.7871 |
| 0.4129 | 4.0 | 12272 | 0.5736 | 0.7835 |
| 0.365 | 5.0 | 15340 | 0.5782 | 0.7964 |
| 0.3202 | 6.0 | 18408 | 0.6482 | 0.7847 |
| 0.2842 | 7.0 | 21476 | 0.6565 | 0.7900 |
| 0.2533 | 8.0 | 24544 | 0.7211 | 0.7912 |
| 0.2278 | 9.0 | 27612 | 0.7751 | 0.7815 |
| 0.2102 | 10.0 | 30680 | 0.7896 | 0.7839 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1