|
--- |
|
license: apache-2.0 |
|
tags: |
|
- text-classification |
|
- generated_from_trainer |
|
datasets: |
|
- xnli |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: xnli_m_bert_only_ar |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: xnli |
|
type: xnli |
|
config: ar |
|
split: train |
|
args: ar |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7080321285140563 |
|
--- |
|
|
|
<!-- 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_ar |
|
|
|
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: 1.3353 |
|
- Accuracy: 0.7080 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.7262 | 1.0 | 3068 | 0.7710 | 0.6715 | |
|
| 0.6461 | 2.0 | 6136 | 0.7109 | 0.6984 | |
|
| 0.563 | 3.0 | 9204 | 0.7325 | 0.7052 | |
|
| 0.4802 | 4.0 | 12272 | 0.7542 | 0.7100 | |
|
| 0.3985 | 5.0 | 15340 | 0.7598 | 0.7072 | |
|
| 0.325 | 6.0 | 18408 | 0.9285 | 0.6932 | |
|
| 0.2554 | 7.0 | 21476 | 0.9771 | 0.7040 | |
|
| 0.202 | 8.0 | 24544 | 1.0835 | 0.7100 | |
|
| 0.1594 | 9.0 | 27612 | 1.2160 | 0.7056 | |
|
| 0.1273 | 10.0 | 30680 | 1.3353 | 0.7080 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.13.0 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.13.1 |
|
|