---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-base-uncased-cola-lora-epochs-10-lr-0.0005
  results: []
---

<!-- 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-base-uncased-cola-lora-epochs-10-lr-0.0005

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7759
- Matthews Correlation: 0.6347

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 265  | 0.6135          | 0.2906               |
| 0.4571        | 2.0   | 530  | 0.4470          | 0.4851               |
| 0.4571        | 3.0   | 795  | 0.3926          | 0.5648               |
| 0.2553        | 4.0   | 1060 | 0.4631          | 0.5358               |
| 0.2553        | 5.0   | 1325 | 0.4592          | 0.5145               |
| 0.1378        | 6.0   | 1590 | 0.8133          | 0.5608               |
| 0.1378        | 7.0   | 1855 | 0.6745          | 0.6815               |
| 0.081         | 8.0   | 2120 | 0.6891          | 0.6815               |
| 0.081         | 9.0   | 2385 | 0.6823          | 0.6110               |
| 0.0512        | 10.0  | 2650 | 0.7759          | 0.6347               |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3