metadata
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
base_model: bert-base-multilingual-cased
model-index:
- name: xnli_m_bert_only_ru
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: xnli
type: xnli
config: ru
split: train
args: ru
metrics:
- type: accuracy
value: 0.7192771084337349
name: Accuracy
xnli_m_bert_only_ru
This model is a fine-tuned version of 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