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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: hBERTv2_new_pretrain_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: 0.7034313725490197 |
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- name: F1 |
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type: f1 |
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value: 0.8118195956454122 |
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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_mrpc |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5990 |
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- Accuracy: 0.7034 |
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- F1: 0.8118 |
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- Combined Score: 0.7576 |
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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 | F1 | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.6721 | 1.0 | 29 | 0.6200 | 0.6838 | 0.8122 | 0.7480 | |
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| 0.6229 | 2.0 | 58 | 0.6098 | 0.6569 | 0.7255 | 0.6912 | |
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| 0.5689 | 3.0 | 87 | 0.5990 | 0.7034 | 0.8118 | 0.7576 | |
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| 0.4615 | 4.0 | 116 | 0.6689 | 0.6765 | 0.78 | 0.7282 | |
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| 0.3475 | 5.0 | 145 | 0.8472 | 0.6054 | 0.6774 | 0.6414 | |
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| 0.2307 | 6.0 | 174 | 0.9917 | 0.6103 | 0.6913 | 0.6508 | |
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| 0.166 | 7.0 | 203 | 1.1149 | 0.6544 | 0.7522 | 0.7033 | |
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| 0.1258 | 8.0 | 232 | 1.3516 | 0.625 | 0.7119 | 0.6684 | |
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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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