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--- |
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library_name: transformers |
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language: |
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- en |
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base_model: gokulsrinivasagan/bert_tiny_olda_book_10_v1 |
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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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- accuracy |
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- f1 |
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model-index: |
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- name: bert_tiny_olda_book_10_v1_qqp |
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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 QQP |
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type: glue |
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args: qqp |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8799901063566659 |
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- name: F1 |
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type: f1 |
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value: 0.841251145138071 |
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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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# bert_tiny_olda_book_10_v1_qqp |
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This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_olda_book_10_v1](https://huggingface.co./gokulsrinivasagan/bert_tiny_olda_book_10_v1) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2816 |
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- Accuracy: 0.8800 |
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- F1: 0.8413 |
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- Combined Score: 0.8606 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | Accuracy | F1 | Combined Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.3941 | 1.0 | 1422 | 0.3365 | 0.8496 | 0.7836 | 0.8166 | |
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| 0.2912 | 2.0 | 2844 | 0.2905 | 0.8710 | 0.8323 | 0.8516 | |
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| 0.2365 | 3.0 | 4266 | 0.2816 | 0.8800 | 0.8413 | 0.8606 | |
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| 0.1917 | 4.0 | 5688 | 0.2965 | 0.8807 | 0.8349 | 0.8578 | |
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| 0.157 | 5.0 | 7110 | 0.3086 | 0.8831 | 0.8474 | 0.8653 | |
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| 0.1268 | 6.0 | 8532 | 0.3240 | 0.8849 | 0.8496 | 0.8672 | |
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| 0.1053 | 7.0 | 9954 | 0.3513 | 0.8878 | 0.8496 | 0.8687 | |
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| 0.0878 | 8.0 | 11376 | 0.3817 | 0.8864 | 0.8520 | 0.8692 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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