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--- |
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language: |
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- en |
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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: hBERTv1_sst2 |
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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 SST2 |
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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: 0.7901376146788991 |
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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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# hBERTv1_sst2 |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the GLUE SST2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4525 |
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- Accuracy: 0.7901 |
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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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| 0.6905 | 1.0 | 264 | 0.6919 | 0.5252 | |
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| 0.6609 | 2.0 | 528 | 0.6088 | 0.6915 | |
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| 0.4152 | 3.0 | 792 | 0.4525 | 0.7901 | |
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| 0.2611 | 4.0 | 1056 | 0.4627 | 0.8096 | |
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| 0.1953 | 5.0 | 1320 | 0.4894 | 0.8073 | |
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| 0.1588 | 6.0 | 1584 | 0.6002 | 0.8016 | |
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| 0.1336 | 7.0 | 1848 | 0.6467 | 0.8062 | |
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| 0.1117 | 8.0 | 2112 | 0.6409 | 0.8062 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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