transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_book base_model:finetune:gokulsrinivasagan/bert_base_lda_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_book_cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.16414986602823045
      name: Matthews Correlation
    - type: accuracy
      value: 0.7056567668914795
      name: Accuracy
---

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# bert_base_lda_book_cola

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_book) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5723
- Matthews Correlation: 0.1641
- Accuracy: 0.7057

## 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 | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6113        | 1.0   | 34   | 0.6214          | 0.0                  | 0.6913   |
| 0.603         | 2.0   | 68   | 0.6130          | 0.0                  | 0.6913   |
| 0.5686        | 3.0   | 102  | 0.5723          | 0.1641               | 0.7057   |
| 0.4955        | 4.0   | 136  | 0.5847          | 0.2300               | 0.7124   |
| 0.4318        | 5.0   | 170  | 0.5832          | 0.2774               | 0.7181   |
| 0.3816        | 6.0   | 204  | 0.7024          | 0.2886               | 0.7325   |
| 0.293         | 7.0   | 238  | 0.7139          | 0.2827               | 0.7124   |
| 0.2447        | 8.0   | 272  | 0.7470          | 0.3125               | 0.7143   |


### Framework versions

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