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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: add_BERT_24_qqp |
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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 QQP |
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type: glue |
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config: qqp |
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split: validation |
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args: qqp |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8048973534504081 |
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- name: F1 |
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type: f1 |
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value: 0.7301771909420538 |
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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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# add_BERT_24_qqp |
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This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4356 |
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- Accuracy: 0.8049 |
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- F1: 0.7302 |
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- Combined Score: 0.7675 |
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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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| 0.5487 | 1.0 | 2843 | 0.5164 | 0.7477 | 0.6465 | 0.6971 | |
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| 0.4981 | 2.0 | 5686 | 0.4939 | 0.7635 | 0.6487 | 0.7061 | |
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| 0.4835 | 3.0 | 8529 | 0.4990 | 0.7568 | 0.6143 | 0.6856 | |
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| 0.4719 | 4.0 | 11372 | 0.4912 | 0.7637 | 0.6417 | 0.7027 | |
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| 0.4632 | 5.0 | 14215 | 0.4881 | 0.7680 | 0.6619 | 0.7150 | |
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| 0.4584 | 6.0 | 17058 | 0.4839 | 0.7679 | 0.6580 | 0.7129 | |
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| 0.4425 | 7.0 | 19901 | 0.4774 | 0.7723 | 0.6914 | 0.7319 | |
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| 0.4308 | 8.0 | 22744 | 0.4679 | 0.7738 | 0.6650 | 0.7194 | |
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| 0.4102 | 9.0 | 25587 | 0.4536 | 0.7873 | 0.6914 | 0.7393 | |
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| 0.3909 | 10.0 | 28430 | 0.4512 | 0.7895 | 0.7153 | 0.7524 | |
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| 0.3787 | 11.0 | 31273 | 0.4681 | 0.7959 | 0.7134 | 0.7547 | |
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| 0.3538 | 12.0 | 34116 | 0.4487 | 0.7981 | 0.7095 | 0.7538 | |
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| 0.3313 | 13.0 | 36959 | 0.4356 | 0.8049 | 0.7302 | 0.7675 | |
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| 0.3053 | 14.0 | 39802 | 0.4410 | 0.8081 | 0.7448 | 0.7764 | |
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| 0.2785 | 15.0 | 42645 | 0.4896 | 0.7942 | 0.7450 | 0.7696 | |
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| 0.2516 | 16.0 | 45488 | 0.4969 | 0.8055 | 0.7510 | 0.7782 | |
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| 0.2254 | 17.0 | 48331 | 0.5079 | 0.8129 | 0.7535 | 0.7832 | |
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| 0.2017 | 18.0 | 51174 | 0.5186 | 0.8113 | 0.7560 | 0.7836 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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