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Librarian Bot: Add base_model information to model (#1)
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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
widget:
- text: The cat sat on the mat.
example_title: Correct grammatical sentence
- text: Me and my friend going to the store.
example_title: Incorrect subject-verb agreement
- text: I ain't got no money.
example_title: Incorrect verb conjugation and double negative
- text: She don't like pizza no more.
example_title: Incorrect verb conjugation and double negative
- text: They is arriving tomorrow.
example_title: Incorrect verb conjugation
base_model: google/electra-small-discriminator
model-index:
- name: electra-small-discriminator-CoLA
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE COLA
type: glue
config: cola
split: validation
args: cola
metrics:
- type: matthews_correlation
value: 0.5510400717227824
name: Matthews Correlation
---
# electra-small-discriminator-CoLA
This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4403
- Matthews Correlation: 0.5510
## Model description
trying to optimize accuracy/speed:
```json
{
"epoch": 8.0,
"eval_loss": 0.4402828514575958,
"eval_matthews_correlation": 0.5510400717227824,
"eval_runtime": 0.9341,
"eval_samples": 1043,
"eval_samples_per_second": 1116.545,
"eval_steps_per_second": 70.654
}
```
## 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: 8e-05
- train_batch_size: 512
- eval_batch_size: 16
- seed: 32754
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 8.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6139 | 1.0 | 17 | 0.5997 | 0.0 |
| 0.5315 | 2.0 | 34 | 0.4890 | 0.5154 |
| 0.4244 | 3.0 | 51 | 0.4469 | 0.5433 |
| 0.3568 | 4.0 | 68 | 0.4403 | 0.5510 |
| 0.319 | 5.0 | 85 | 0.4517 | 0.5654 |
| 0.2887 | 6.0 | 102 | 0.4656 | 0.5728 |
| 0.2771 | 7.0 | 119 | 0.4558 | 0.5883 |
| 0.2729 | 8.0 | 136 | 0.4569 | 0.5858 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1