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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_sa_GLUE_Experiment_logit_kd_pretrain_mnli
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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: mnli
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split: validation_matched
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args: mnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.817524197656648
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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_sa_GLUE_Experiment_logit_kd_pretrain_mnli
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This model is a fine-tuned version of [gokuls/distilbert_sa_pre-training-complete](https://huggingface.co/gokuls/distilbert_sa_pre-training-complete) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3990
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- Accuracy: 0.8175
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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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| 0.4379 | 1.0 | 1534 | 0.3984 | 0.7976 |
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| 0.3845 | 2.0 | 3068 | 0.3953 | 0.8047 |
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| 0.359 | 3.0 | 4602 | 0.3935 | 0.8102 |
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| 0.3411 | 4.0 | 6136 | 0.3962 | 0.8077 |
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| 0.3279 | 5.0 | 7670 | 0.3959 | 0.8172 |
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| 0.3189 | 6.0 | 9204 | 0.4018 | 0.8102 |
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| 0.3119 | 7.0 | 10738 | 0.4040 | 0.8073 |
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| 0.3071 | 8.0 | 12272 | 0.3990 | 0.8175 |
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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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