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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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- f1 |
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model-index: |
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- name: hBERTv1_mrpc |
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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 MRPC |
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type: glue |
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config: mrpc |
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split: validation |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6862745098039216 |
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- name: F1 |
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type: f1 |
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value: 0.7999999999999999 |
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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_mrpc |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6051 |
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- Accuracy: 0.6863 |
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- F1: 0.8000 |
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- Combined Score: 0.7431 |
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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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- 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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- mixed_precision_training: Native AMP |
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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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| 0.6536 | 1.0 | 15 | 0.6243 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6275 | 2.0 | 30 | 0.6174 | 0.7010 | 0.8117 | 0.7564 | |
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| 0.6129 | 3.0 | 45 | 0.6089 | 0.6961 | 0.8182 | 0.7571 | |
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| 0.6087 | 4.0 | 60 | 0.6062 | 0.6887 | 0.8130 | 0.7508 | |
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| 0.5939 | 5.0 | 75 | 0.6104 | 0.6863 | 0.7935 | 0.7399 | |
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| 0.5707 | 6.0 | 90 | 0.6184 | 0.7083 | 0.8183 | 0.7633 | |
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| 0.5426 | 7.0 | 105 | 0.6051 | 0.6863 | 0.8000 | 0.7431 | |
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| 0.4819 | 8.0 | 120 | 0.6560 | 0.6936 | 0.8019 | 0.7478 | |
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| 0.4279 | 9.0 | 135 | 0.6673 | 0.6887 | 0.7678 | 0.7283 | |
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| 0.3374 | 10.0 | 150 | 0.8092 | 0.6863 | 0.7902 | 0.7382 | |
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| 0.2789 | 11.0 | 165 | 0.9342 | 0.6887 | 0.7935 | 0.7411 | |
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| 0.2216 | 12.0 | 180 | 0.9708 | 0.6838 | 0.7810 | 0.7324 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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