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add_BERT_24_qqp

Text Classification
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hybridbert
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+ ---
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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
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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: 0.8112787534009399
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+ - name: F1
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+ type: f1
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+ value: 0.7559961624560281
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+ ---
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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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+
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+ # add_BERT_24_qqp
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+
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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 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5186
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+ - Accuracy: 0.8113
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+ - F1: 0.7560
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+ - Combined Score: 0.7836
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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