metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_xlm_r_only_sw
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: sw
split: train
args: sw
metrics:
- name: Accuracy
type: accuracy
value: 0.6903614457831325
xnli_xlm_r_only_sw
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: 0.9651
- Accuracy: 0.6904
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 |
|---|---|---|---|---|
| 0.8628 | 1.0 | 3068 | 0.7719 | 0.6659 |
| 0.7407 | 2.0 | 6136 | 0.7147 | 0.6944 |
| 0.6791 | 3.0 | 9204 | 0.7591 | 0.6940 |
| 0.6293 | 4.0 | 12272 | 0.7538 | 0.6968 |
| 0.5833 | 5.0 | 15340 | 0.7716 | 0.6988 |
| 0.5425 | 6.0 | 18408 | 0.8323 | 0.6956 |
| 0.5029 | 7.0 | 21476 | 0.8407 | 0.6948 |
| 0.4707 | 8.0 | 24544 | 0.8840 | 0.6908 |
| 0.4437 | 9.0 | 27612 | 0.9506 | 0.6880 |
| 0.4234 | 10.0 | 30680 | 0.9651 | 0.6904 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1