transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_5_v1 base_model:finetune:gokulsrinivasagan/bert_tiny_lda_5_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_5_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_5_v1_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
---

<!-- 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. -->

# bert_tiny_lda_5_v1_cola

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_5_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_5_v1) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6138
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6154        | 1.0   | 34   | 0.6138          | 0.0                  | 0.6913   |
| 0.5986        | 2.0   | 68   | 0.6147          | 0.0064               | 0.6865   |
| 0.5752        | 3.0   | 102  | 0.6158          | 0.0616               | 0.6894   |
| 0.5356        | 4.0   | 136  | 0.6378          | 0.1110               | 0.6807   |
| 0.4841        | 5.0   | 170  | 0.6615          | 0.0969               | 0.6721   |
| 0.4382        | 6.0   | 204  | 0.7818          | 0.0896               | 0.6673   |


### Framework versions

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