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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_emb_com_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: 0.789463269849122 |
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- name: F1 |
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type: f1 |
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value: 0.7288135593220338 |
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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_emb_com_qqp |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48) on the GLUE QQP dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4383 |
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- Accuracy: 0.7895 |
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- F1: 0.7288 |
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- Combined Score: 0.7591 |
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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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| 0.5492 | 1.0 | 2843 | 0.5130 | 0.7537 | 0.6393 | 0.6965 | |
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| 0.4928 | 2.0 | 5686 | 0.4971 | 0.7602 | 0.6526 | 0.7064 | |
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| 0.4578 | 3.0 | 8529 | 0.4656 | 0.7775 | 0.6825 | 0.7300 | |
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| 0.4346 | 4.0 | 11372 | 0.4565 | 0.7804 | 0.6744 | 0.7274 | |
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| 0.4146 | 5.0 | 14215 | 0.4783 | 0.7812 | 0.7078 | 0.7445 | |
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| 0.3952 | 6.0 | 17058 | 0.4675 | 0.7899 | 0.7042 | 0.7470 | |
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| 0.3747 | 7.0 | 19901 | 0.4383 | 0.7895 | 0.7288 | 0.7591 | |
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| 0.355 | 8.0 | 22744 | 0.4455 | 0.7948 | 0.7053 | 0.7500 | |
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| 0.3362 | 9.0 | 25587 | 0.4483 | 0.7935 | 0.7334 | 0.7635 | |
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| 0.3185 | 10.0 | 28430 | 0.4480 | 0.7956 | 0.7388 | 0.7672 | |
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| 0.301 | 11.0 | 31273 | 0.4630 | 0.8055 | 0.7236 | 0.7646 | |
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| 0.2848 | 12.0 | 34116 | 0.4850 | 0.8062 | 0.7352 | 0.7707 | |
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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 2.12.0 |
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- Tokenizers 0.13.3 |
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