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---
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_xlm_r_only_ur
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: ur
split: train
args: ur
metrics:
- name: Accuracy
type: accuracy
value: 0.6514056224899598
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xnli_xlm_r_only_ur
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8516
- Accuracy: 0.6514
## 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: 1.5e-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: 1000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0129 | 1.0 | 3068 | 0.8285 | 0.6357 |
| 0.9628 | 2.0 | 6136 | 0.8120 | 0.6470 |
| 0.9407 | 3.0 | 9204 | 0.7934 | 0.6643 |
| 0.9205 | 4.0 | 12272 | 0.7802 | 0.6546 |
| 0.9001 | 5.0 | 15340 | 0.7820 | 0.6594 |
| 0.8791 | 6.0 | 18408 | 0.8046 | 0.6502 |
| 0.8593 | 7.0 | 21476 | 0.7950 | 0.6627 |
| 0.8404 | 8.0 | 24544 | 0.8231 | 0.6514 |
| 0.8242 | 9.0 | 27612 | 0.8376 | 0.6558 |
| 0.8118 | 10.0 | 30680 | 0.8516 | 0.6514 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
|