masterkristall
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End of training
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README.md
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---
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license: apache-2.0
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base_model: google/bert_uncased_L-2_H-128_A-2
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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: bert_distillation_0
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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: sst2
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split: validation
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args: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8302752293577982
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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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# bert_distillation_0
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1784
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- Accuracy: 0.8303
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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: 0.0001
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 2023
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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: 7
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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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| 1.2697 | 1.0 | 527 | 1.0445 | 0.8200 |
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| 0.6784 | 2.0 | 1054 | 1.0168 | 0.8177 |
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| 0.5206 | 3.0 | 1581 | 1.1356 | 0.8108 |
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| 0.4383 | 4.0 | 2108 | 1.1437 | 0.8280 |
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| 0.3844 | 5.0 | 2635 | 1.1687 | 0.8268 |
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| 0.3547 | 6.0 | 3162 | 1.1784 | 0.8303 |
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| 0.3373 | 7.0 | 3689 | 1.2045 | 0.8280 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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size 8281
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