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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_base_lda_5 |
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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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model-index: |
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- name: bert_base_lda_5_wnli |
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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 WNLI |
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type: glue |
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args: wnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5633802816901409 |
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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_base_lda_5_wnli |
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This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5) on the GLUE WNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6849 |
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- Accuracy: 0.5634 |
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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: 0.001 |
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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 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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.121 | 1.0 | 3 | 0.8205 | 0.5634 | |
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| 1.6034 | 2.0 | 6 | 1.7293 | 0.4366 | |
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| 0.9483 | 3.0 | 9 | 0.7649 | 0.4366 | |
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| 0.7514 | 4.0 | 12 | 0.7557 | 0.5634 | |
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| 0.746 | 5.0 | 15 | 0.8105 | 0.4366 | |
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| 0.7896 | 6.0 | 18 | 0.7383 | 0.4366 | |
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| 0.7573 | 7.0 | 21 | 0.6853 | 0.5634 | |
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| 0.6951 | 8.0 | 24 | 0.8346 | 0.4366 | |
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| 0.746 | 9.0 | 27 | 0.6906 | 0.5634 | |
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| 0.6992 | 10.0 | 30 | 0.6849 | 0.5634 | |
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| 0.6942 | 11.0 | 33 | 0.7009 | 0.4366 | |
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| 0.7 | 12.0 | 36 | 0.6951 | 0.4366 | |
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| 0.6976 | 13.0 | 39 | 0.6854 | 0.5634 | |
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| 0.6999 | 14.0 | 42 | 0.6901 | 0.5634 | |
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| 0.6948 | 15.0 | 45 | 0.6926 | 0.5634 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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