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_th
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: xnli
type: xnli
config: th
split: train
args: th
metrics:
- type: accuracy
value: 0.6277108433734939
name: Accuracy
xnli_m_bert_only_th
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: 1.4266
- Accuracy: 0.6277
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 |
|---|---|---|---|---|
| 0.7447 | 1.0 | 3068 | 0.8675 | 0.6205 |
| 0.6763 | 2.0 | 6136 | 0.8060 | 0.6602 |
| 0.6124 | 3.0 | 9204 | 0.8229 | 0.6586 |
| 0.5476 | 4.0 | 12272 | 0.8333 | 0.6542 |
| 0.4817 | 5.0 | 15340 | 0.8520 | 0.6618 |
| 0.4128 | 6.0 | 18408 | 0.9734 | 0.6426 |
| 0.3436 | 7.0 | 21476 | 1.0549 | 0.6365 |
| 0.2828 | 8.0 | 24544 | 1.1406 | 0.6321 |
| 0.2272 | 9.0 | 27612 | 1.3150 | 0.6301 |
| 0.1852 | 10.0 | 30680 | 1.4266 | 0.6277 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1