metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_xlm_r_only_de
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: de
split: train
args: de
metrics:
- name: Accuracy
type: accuracy
value: 0.7863453815261044
xnli_xlm_r_only_de
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: 0.7212
- Accuracy: 0.7863
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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.6876 | 1.0 | 3068 | 0.7671 | 0.5670 |
| 0.5323 | 2.0 | 6136 | 0.7972 | 0.5189 |
| 0.4652 | 3.0 | 9204 | 0.7928 | 0.5346 |
| 0.4089 | 4.0 | 12272 | 0.7940 | 0.5392 |
| 0.3614 | 5.0 | 15340 | 0.8092 | 0.5477 |
| 0.3173 | 6.0 | 18408 | 0.7920 | 0.6186 |
| 0.2805 | 7.0 | 21476 | 0.7936 | 0.6323 |
| 0.2496 | 8.0 | 24544 | 0.7960 | 0.6574 |
| 0.2246 | 9.0 | 27612 | 0.6894 | 0.7880 |
| 0.2068 | 10.0 | 30680 | 0.7212 | 0.7863 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1