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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- matthews_correlation
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model-index:
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- name: cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# cola-pixel-handwritten-mean-vatrpp-256-64-4-5e-5-15000-42
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This model is a fine-tuned version of [noniewiem/pixel-handwritten](https://huggingface.co/noniewiem/pixel-handwritten) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7009
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- Matthews Correlation: 0.0757
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 64
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 200
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- training_steps: 15000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
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| 0.6426 | 3.03 | 100 | 0.6255 | 0.0 |
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| 0.6176 | 6.06 | 200 | 0.6308 | 0.0 |
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| 0.6183 | 9.09 | 300 | 0.6187 | 0.0 |
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| 0.6162 | 12.12 | 400 | 0.6158 | 0.0 |
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| 0.614 | 15.15 | 500 | 0.6250 | -0.0293 |
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| 0.6096 | 18.18 | 600 | 0.6185 | 0.0 |
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| 0.6055 | 21.21 | 700 | 0.6224 | 0.0175 |
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| 0.6001 | 24.24 | 800 | 0.6551 | 0.1301 |
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| 0.5909 | 27.27 | 900 | 0.6534 | 0.0566 |
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| 0.5726 | 30.3 | 1000 | 0.6679 | 0.1029 |
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| 0.5524 | 33.33 | 1100 | 0.6901 | 0.0631 |
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| 0.5167 | 36.36 | 1200 | 0.7027 | 0.0948 |
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| 0.4779 | 39.39 | 1300 | 0.7578 | 0.1012 |
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| 0.4271 | 42.42 | 1400 | 0.8021 | 0.1108 |
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| 0.3888 | 45.45 | 1500 | 0.8813 | 0.1025 |
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| 0.3428 | 48.48 | 1600 | 0.9362 | 0.1437 |
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| 0.2977 | 51.51 | 1700 | 1.0786 | 0.1118 |
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| 0.2642 | 54.54 | 1800 | 1.0610 | 0.0901 |
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| 0.2272 | 57.57 | 1900 | 1.1835 | 0.1155 |
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| 0.1915 | 60.6 | 2000 | 1.2531 | 0.1224 |
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| 0.1691 | 63.63 | 2100 | 1.3903 | 0.0754 |
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| 0.1491 | 66.66 | 2200 | 1.4947 | 0.0674 |
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| 0.1339 | 69.69 | 2300 | 1.5434 | 0.0736 |
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| 0.1164 | 72.72 | 2400 | 1.5793 | 0.1165 |
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| 0.1078 | 75.75 | 2500 | 1.5938 | 0.0995 |
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| 0.0974 | 78.78 | 2600 | 1.7009 | 0.0757 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.0.0
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- Tokenizers 0.13.3
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