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--- |
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language: |
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- en |
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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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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE COLA |
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type: glue |
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args: cola |
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metrics: |
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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.07568068132313144 |
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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 COLA 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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