|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- en |
|
|
base_model: Hartunka/bert_base_km_20_v2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- glue |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: bert_base_km_20_v2_mnli |
|
|
results: |
|
|
- task: |
|
|
name: Text Classification |
|
|
type: text-classification |
|
|
dataset: |
|
|
name: GLUE MNLI |
|
|
type: glue |
|
|
args: mnli |
|
|
metrics: |
|
|
- name: Accuracy |
|
|
type: accuracy |
|
|
value: 0.6644629780309195 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# bert_base_km_20_v2_mnli |
|
|
|
|
|
This model is a fine-tuned version of [Hartunka/bert_base_km_20_v2](https://huggingface.co/Hartunka/bert_base_km_20_v2) on the GLUE MNLI dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.7873 |
|
|
- Accuracy: 0.6645 |
|
|
|
|
|
## 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: 256 |
|
|
- eval_batch_size: 256 |
|
|
- seed: 10 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 50 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
|
| 0.9876 | 1.0 | 1534 | 0.9146 | 0.5727 | |
|
|
| 0.8776 | 2.0 | 3068 | 0.8655 | 0.6046 | |
|
|
| 0.7975 | 3.0 | 4602 | 0.8097 | 0.6418 | |
|
|
| 0.7185 | 4.0 | 6136 | 0.8000 | 0.6566 | |
|
|
| 0.6415 | 5.0 | 7670 | 0.7951 | 0.6616 | |
|
|
| 0.5611 | 6.0 | 9204 | 0.8547 | 0.6600 | |
|
|
| 0.4782 | 7.0 | 10738 | 0.9200 | 0.6601 | |
|
|
| 0.3996 | 8.0 | 12272 | 1.0102 | 0.6587 | |
|
|
| 0.3293 | 9.0 | 13806 | 1.1861 | 0.6507 | |
|
|
| 0.2684 | 10.0 | 15340 | 1.2364 | 0.6570 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.50.2 |
|
|
- Pytorch 2.2.1+cu121 |
|
|
- Datasets 2.18.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
