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bert_base_km_100_v2_cola
Hartunka/bert_base_km_100_v2_cola
bert_base_km_100_v2_cola is a text classification model from Hartunka. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Apr 23, 2025
- Updated
- Apr 23, 2025
- SHA
- c9873965
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert_base_km_100_v2_cola
This model is a fine-tuned version of Hartunka/bert_base_km_100_v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6174
- Matthews Correlation: 0.0
- Accuracy: 0.6913
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.6144 | 1.0 | 34 | 0.6174 | 0.0 | 0.6913 |
| 0.5971 | 2.0 | 68 | 0.6221 | 0.0407 | 0.6913 |
| 0.566 | 3.0 | 102 | 0.6273 | 0.1041 | 0.6913 |
| 0.5216 | 4.0 | 136 | 0.6422 | 0.0595 | 0.6587 |
| 0.4534 | 5.0 | 170 | 0.6912 | 0.0983 | 0.6673 |
| 0.3795 | 6.0 | 204 | 0.7572 | 0.1157 | 0.6443 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Apr 23, 2025
- Updated
- Apr 23, 2025