|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- matthews_correlation |
|
model-index: |
|
- name: distilbert-base-uncased-finetuned-cola |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: glue |
|
type: glue |
|
config: cola |
|
split: validation |
|
args: cola |
|
metrics: |
|
- name: Matthews Correlation |
|
type: matthews_correlation |
|
value: 0.5471613867597194 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distilbert-base-uncased-finetuned-cola |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7833 |
|
- Matthews Correlation: 0.5472 |
|
|
|
## 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: 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------------------:| |
|
| 0.5216 | 1.0 | 535 | 0.5186 | 0.4153 | |
|
| 0.3502 | 2.0 | 1070 | 0.5054 | 0.5065 | |
|
| 0.2402 | 3.0 | 1605 | 0.5903 | 0.5275 | |
|
| 0.1843 | 4.0 | 2140 | 0.7420 | 0.5370 | |
|
| 0.1347 | 5.0 | 2675 | 0.7833 | 0.5472 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.13.0 |
|
- Tokenizers 0.13.3 |
|
|
