metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_xlm_r_only_ru
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: ru
split: train
args: ru
metrics:
- name: Accuracy
type: accuracy
value: 0.7590361445783133
xnli_xlm_r_only_ru
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: 0.9127
- Accuracy: 0.7590
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 |
|---|---|---|---|---|
| 0.6832 | 1.0 | 3068 | 0.6479 | 0.7378 |
| 0.5448 | 2.0 | 6136 | 0.5704 | 0.7763 |
| 0.4795 | 3.0 | 9204 | 0.6443 | 0.7614 |
| 0.4243 | 4.0 | 12272 | 0.6487 | 0.7635 |
| 0.3745 | 5.0 | 15340 | 0.6636 | 0.7627 |
| 0.3313 | 6.0 | 18408 | 0.7397 | 0.7631 |
| 0.2929 | 7.0 | 21476 | 0.7849 | 0.7618 |
| 0.2608 | 8.0 | 24544 | 0.8279 | 0.7566 |
| 0.2369 | 9.0 | 27612 | 0.8860 | 0.7606 |
| 0.2183 | 10.0 | 30680 | 0.9127 | 0.7590 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1