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metadata
language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - matthews_correlation
model-index:
  - name: cola-pixel-handwritten-mean-vatrpp-256-64-4-2e-5-15000-42
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE COLA
          type: glue
          args: cola
        metrics:
          - name: Matthews Correlation
            type: matthews_correlation
            value: 0

cola-pixel-handwritten-mean-vatrpp-256-64-4-2e-5-15000-42

This model is a fine-tuned version of noniewiem/pixel-handwritten on the GLUE COLA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6182
  • Matthews Correlation: 0.0

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: 2e-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
0.655 3.03 100 0.6341 0.0029
0.6174 6.06 200 0.6282 0.0
0.6196 9.09 300 0.6198 0.0
0.6158 12.12 400 0.6199 0.0
0.6175 15.15 500 0.6181 0.0
0.6152 18.18 600 0.6191 0.0
0.617 21.21 700 0.6185 0.0
0.6191 24.24 800 0.6185 0.0
0.6162 27.27 900 0.6183 0.0
0.6166 30.3 1000 0.6183 0.0
0.6177 33.33 1100 0.6182 0.0

Framework versions

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