|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-multilingual-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: 20231005-8-bert-base-multilingual-cased-new |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# 20231005-8-bert-base-multilingual-cased-new |
|
|
|
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Accuracy: 0.6178 |
|
- Loss: 1.5315 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
|
|:-------------:|:-----:|:----:|:--------:|:---------------:| |
|
| 2.9965 | 1.82 | 200 | 0.4212 | 2.5494 | |
|
| 2.5203 | 3.64 | 400 | 0.4747 | 2.4152 | |
|
| 2.3137 | 5.45 | 600 | 0.4965 | 1.9514 | |
|
| 2.1441 | 7.27 | 800 | 0.5762 | 1.9575 | |
|
| 2.0708 | 9.09 | 1000 | 0.5794 | 1.7864 | |
|
| 2.0004 | 10.91 | 1200 | 0.5336 | 1.9741 | |
|
| 1.9093 | 12.73 | 1400 | 0.6217 | 1.7001 | |
|
| 1.8906 | 14.55 | 1600 | 0.5589 | 1.8629 | |
|
| 1.7744 | 16.36 | 1800 | 0.5996 | 1.5749 | |
|
| 1.7698 | 18.18 | 2000 | 0.6288 | 1.6576 | |
|
| 1.7274 | 20.0 | 2200 | 0.6178 | 1.5315 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
