pytorch pixel generated_from_trainer en dataset:glue model-index region:us
---
datasets:
- glue
language:
- en
metrics:
- matthews_correlation
tags:
- generated_from_trainer
model-index:
- name: cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.07568068132313144
      name: Matthews Correlation
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42

This model is a fine-tuned version of [noniewiem/pixel-handwritten](https://huggingface.co/noniewiem/pixel-handwritten) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7009
- Matthews Correlation: 0.0757

## 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: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6426        | 3.03  | 100  | 0.6255          | 0.0                  |
| 0.6176        | 6.06  | 200  | 0.6308          | 0.0                  |
| 0.6183        | 9.09  | 300  | 0.6187          | 0.0                  |
| 0.6162        | 12.12 | 400  | 0.6158          | 0.0                  |
| 0.614         | 15.15 | 500  | 0.6250          | -0.0293              |
| 0.6096        | 18.18 | 600  | 0.6185          | 0.0                  |
| 0.6055        | 21.21 | 700  | 0.6224          | 0.0175               |
| 0.6001        | 24.24 | 800  | 0.6551          | 0.1301               |
| 0.5909        | 27.27 | 900  | 0.6534          | 0.0566               |
| 0.5726        | 30.3  | 1000 | 0.6679          | 0.1029               |
| 0.5524        | 33.33 | 1100 | 0.6901          | 0.0631               |
| 0.5167        | 36.36 | 1200 | 0.7027          | 0.0948               |
| 0.4779        | 39.39 | 1300 | 0.7578          | 0.1012               |
| 0.4271        | 42.42 | 1400 | 0.8021          | 0.1108               |
| 0.3888        | 45.45 | 1500 | 0.8813          | 0.1025               |
| 0.3428        | 48.48 | 1600 | 0.9362          | 0.1437               |
| 0.2977        | 51.51 | 1700 | 1.0786          | 0.1118               |
| 0.2642        | 54.54 | 1800 | 1.0610          | 0.0901               |
| 0.2272        | 57.57 | 1900 | 1.1835          | 0.1155               |
| 0.1915        | 60.6  | 2000 | 1.2531          | 0.1224               |
| 0.1691        | 63.63 | 2100 | 1.3903          | 0.0754               |
| 0.1491        | 66.66 | 2200 | 1.4947          | 0.0674               |
| 0.1339        | 69.69 | 2300 | 1.5434          | 0.0736               |
| 0.1164        | 72.72 | 2400 | 1.5793          | 0.1165               |
| 0.1078        | 75.75 | 2500 | 1.5938          | 0.0995               |
| 0.0974        | 78.78 | 2600 | 1.7009          | 0.0757               |


### Framework versions

- Transformers 4.17.0
- Pytorch 2.3.0+cu121
- Datasets 2.0.0
- Tokenizers 0.13.3
