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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_new_pretrain_48_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: 0.7058823529411765 |
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- name: F1 |
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type: f1 |
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value: 0.8058252427184466 |
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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_new_pretrain_48_mrpc |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5714 |
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- Accuracy: 0.7059 |
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- F1: 0.8058 |
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- Combined Score: 0.7559 |
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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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| 0.6764 | 1.0 | 29 | 0.5974 | 0.6887 | 0.8096 | 0.7492 | |
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| 0.6341 | 2.0 | 58 | 0.6032 | 0.6838 | 0.7962 | 0.7400 | |
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| 0.5778 | 3.0 | 87 | 0.5714 | 0.7059 | 0.8058 | 0.7559 | |
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| 0.4891 | 4.0 | 116 | 0.6448 | 0.7132 | 0.8104 | 0.7618 | |
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| 0.3469 | 5.0 | 145 | 0.8814 | 0.6593 | 0.7504 | 0.7049 | |
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| 0.2429 | 6.0 | 174 | 0.8431 | 0.6740 | 0.7654 | 0.7197 | |
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| 0.1749 | 7.0 | 203 | 1.0049 | 0.7010 | 0.7918 | 0.7464 | |
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| 0.1434 | 8.0 | 232 | 1.1036 | 0.6765 | 0.7634 | 0.7200 | |
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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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