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masterkristall
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bert_distillation_tiny

Text Classification
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  1. README.md +82 -0
  2. logs/events.out.tfevents.1701202155.62074d9d7b32.1179.2 +2 -2
  3. logs/events.out.tfevents.1701202309.62074d9d7b32.1179.3 +3 -0
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README.md ADDED
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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_tiny
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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: 0.8256880733944955
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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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+ # bert_distillation_tiny
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+
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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: 0.4274
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+ - Accuracy: 0.8257
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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: 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4139 | 1.0 | 527 | 0.4204 | 0.8096 |
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+ | 0.27 | 2.0 | 1054 | 0.4274 | 0.8257 |
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+ | 0.2226 | 3.0 | 1581 | 0.4899 | 0.8245 |
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+ | 0.1931 | 4.0 | 2108 | 0.4961 | 0.8222 |
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+ | 0.1732 | 5.0 | 2635 | 0.5302 | 0.8222 |
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+ | 0.1608 | 6.0 | 3162 | 0.5393 | 0.8234 |
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+ | 0.152 | 7.0 | 3689 | 0.5562 | 0.8177 |
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+
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+
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+ ### Framework versions
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+
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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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