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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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- accuracy |
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model-index: |
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- name: hBERTv1_new_pretrain_48_cola |
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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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config: cola |
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split: validation |
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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: 0.0 |
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- name: Accuracy |
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type: accuracy |
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value: 0.6912751793861389 |
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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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# hBERTv1_new_pretrain_48_cola |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6153 |
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- Matthews Correlation: 0.0 |
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- Accuracy: 0.6913 |
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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: 4e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| |
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| 0.6296 | 1.0 | 67 | 0.6343 | 0.0 | 0.6913 | |
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| 0.6166 | 2.0 | 134 | 0.6423 | 0.0 | 0.6913 | |
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| 0.611 | 3.0 | 201 | 0.6202 | 0.0 | 0.6913 | |
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| 0.6085 | 4.0 | 268 | 0.6188 | 0.0 | 0.6913 | |
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| 0.6107 | 5.0 | 335 | 0.6153 | 0.0 | 0.6913 | |
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| 0.5988 | 6.0 | 402 | 0.6260 | 0.0 | 0.6913 | |
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| 0.5826 | 7.0 | 469 | 0.6354 | 0.0 | 0.6913 | |
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| 0.5536 | 8.0 | 536 | 0.6534 | 0.0304 | 0.6539 | |
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| 0.5402 | 9.0 | 603 | 0.6798 | 0.0917 | 0.5954 | |
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| 0.5341 | 10.0 | 670 | 0.7670 | 0.0513 | 0.6836 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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