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README.md
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---
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license: apache-2.0
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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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model-index:
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- name: distilbert_add_GLUE_Experiment_logit_kd_qnli_96
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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: qnli
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split: validation
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args: qnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5722130697419
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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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# distilbert_add_GLUE_Experiment_logit_kd_qnli_96
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4074
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- Accuracy: 0.5722
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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: 5e-05
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- train_batch_size: 256
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- eval_batch_size: 256
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4153 | 1.0 | 410 | 0.4114 | 0.5054 |
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| 0.4152 | 2.0 | 820 | 0.4115 | 0.5054 |
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| 0.4129 | 3.0 | 1230 | 0.4020 | 0.5686 |
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| 0.3995 | 4.0 | 1640 | 0.3984 | 0.5806 |
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| 0.3934 | 5.0 | 2050 | 0.3992 | 0.5794 |
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| 0.3888 | 6.0 | 2460 | 0.4024 | 0.5810 |
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| 0.385 | 7.0 | 2870 | 0.4105 | 0.5675 |
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| 0.3808 | 8.0 | 3280 | 0.4050 | 0.5777 |
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| 0.3768 | 9.0 | 3690 | 0.4074 | 0.5722 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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