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---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_m_bert_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: 0.7192771084337349
---
<!-- 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_m_bert_only_ru
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4375
- Accuracy: 0.7193
## 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: 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
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6663 | 1.0 | 3068 | 0.7367 | 0.6908 |
| 0.5792 | 2.0 | 6136 | 0.6650 | 0.7229 |
| 0.4875 | 3.0 | 9204 | 0.6935 | 0.7285 |
| 0.3989 | 4.0 | 12272 | 0.7481 | 0.7233 |
| 0.3177 | 5.0 | 15340 | 0.7786 | 0.7277 |
| 0.2429 | 6.0 | 18408 | 0.9419 | 0.7209 |
| 0.1871 | 7.0 | 21476 | 1.0537 | 0.7237 |
| 0.1388 | 8.0 | 24544 | 1.1777 | 0.7225 |
| 0.106 | 9.0 | 27612 | 1.3488 | 0.7209 |
| 0.0776 | 10.0 | 30680 | 1.4375 | 0.7193 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
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