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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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- accuracy |
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model-index: |
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- name: hBERTv2_new_pretrain_48_qnli |
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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 QNLI |
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type: glue |
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config: qnli |
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split: validation |
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args: qnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5967417170053084 |
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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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# hBERTv2_new_pretrain_48_qnli |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE QNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6635 |
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- Accuracy: 0.5967 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6834 | 1.0 | 819 | 0.6635 | 0.5967 | |
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| 0.6634 | 2.0 | 1638 | 0.6696 | 0.5931 | |
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| 0.6597 | 3.0 | 2457 | 0.6701 | 0.6013 | |
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| 0.6607 | 4.0 | 3276 | 0.6780 | 0.5876 | |
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| 0.6602 | 5.0 | 4095 | 0.6903 | 0.5858 | |
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| 0.6577 | 6.0 | 4914 | 0.6712 | 0.5892 | |
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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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