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--- |
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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: minilm-l12-h384-sst2-distilled |
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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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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9220183486238532 |
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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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# minilm-l12-h384-sst2-distilled |
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This model is a fine-tuned version of [nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5417 |
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- Accuracy: 0.9220 |
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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: 0.0001400785945474408 |
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- train_batch_size: 512 |
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- eval_batch_size: 512 |
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- seed: 33 |
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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: 5 |
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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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| 2.2689 | 1.0 | 132 | 0.7102 | 0.8979 | |
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| 0.8295 | 2.0 | 264 | 0.5669 | 0.9117 | |
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| 0.5059 | 3.0 | 396 | 0.5545 | 0.9220 | |
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| 0.3722 | 4.0 | 528 | 0.5378 | 0.9209 | |
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| 0.2924 | 5.0 | 660 | 0.5417 | 0.9220 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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