transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_20 base_model:finetune:gokulsrinivasagan/bert_tiny_lda_20 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_20
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_20_cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.0
      name: Matthews Correlation
    - type: accuracy
      value: 0.6912751793861389
      name: Accuracy
---

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# bert_tiny_lda_20_cola

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6170
- Matthews Correlation: 0.0
- Accuracy: 0.6913

## 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: 0.001
- 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: 30

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:--------:|:---------------:|:--------------------:|
| 0.6222        | 1.0   | 90   | 0.6913   | 0.6256          | 0.0                  |
| 0.6092        | 2.0   | 180  | 0.6913   | 0.6225          | 0.0                  |
| 0.6093        | 3.0   | 270  | 0.6913   | 0.6182          | 0.0                  |
| 0.6121        | 4.0   | 360  | 0.6185   | 0.0             | 0.6913               |
| 0.6122        | 5.0   | 450  | 0.6198   | 0.0             | 0.6913               |
| 0.6125        | 6.0   | 540  | 0.6181   | 0.0             | 0.6913               |
| 0.6076        | 7.0   | 630  | 0.6170   | 0.0             | 0.6913               |
| 0.61          | 8.0   | 720  | 0.6219   | 0.0             | 0.6913               |
| 0.6084        | 9.0   | 810  | 0.6231   | 0.0             | 0.6913               |
| 0.6082        | 10.0  | 900  | 0.6172   | 0.0             | 0.6913               |
| 0.6096        | 11.0  | 990  | 0.6190   | 0.0             | 0.6913               |
| 0.6078        | 12.0  | 1080 | 0.6197   | 0.0             | 0.6913               |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
