|
--- |
|
language: |
|
- en |
|
license: mit |
|
base_model: microsoft/deberta-v3-large |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- matthews_correlation |
|
model-index: |
|
- name: output |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE COLA |
|
type: glue |
|
config: cola |
|
split: validation |
|
args: cola |
|
metrics: |
|
- name: Matthews Correlation |
|
type: matthews_correlation |
|
value: 0.7060783174788182 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# output |
|
|
|
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the GLUE COLA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3123 |
|
- Matthews Correlation: 0.7061 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------------------:| |
|
| 0.3546 | 1.0 | 535 | 0.3123 | 0.7061 | |
|
| 0.2078 | 2.0 | 1070 | 0.3618 | 0.7311 | |
|
| 0.1313 | 3.0 | 1605 | 0.5145 | 0.7160 | |
|
| 0.087 | 4.0 | 2140 | 0.5819 | 0.7230 | |
|
| 0.0597 | 5.0 | 2675 | 0.6325 | 0.7397 | |
|
| 0.0435 | 6.0 | 3210 | 0.6152 | 0.7332 | |
|
| 0.0268 | 7.0 | 3745 | 0.7296 | 0.7327 | |
|
| 0.0304 | 8.0 | 4280 | 0.7672 | 0.7287 | |
|
| 0.015 | 9.0 | 4815 | 0.8067 | 0.7264 | |
|
| 0.0133 | 10.0 | 5350 | 0.8079 | 0.7246 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.0 |
|
|
