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--- |
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language: |
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- en |
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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: mobilebert_add_GLUE_Experiment_logit_kd_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: 0.801605504587156 |
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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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# mobilebert_add_GLUE_Experiment_logit_kd_sst2 |
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE SST2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7778 |
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- Accuracy: 0.8016 |
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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: 128 |
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- eval_batch_size: 128 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.5405 | 1.0 | 527 | 1.4225 | 0.5539 | |
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| 1.3567 | 2.0 | 1054 | 1.4707 | 0.5482 | |
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| 1.2859 | 3.0 | 1581 | 1.4661 | 0.5677 | |
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| 1.2563 | 4.0 | 2108 | 1.4136 | 0.5665 | |
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| 1.2414 | 5.0 | 2635 | 1.4239 | 0.5940 | |
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| 1.2288 | 6.0 | 3162 | 1.4443 | 0.5745 | |
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| 0.7679 | 7.0 | 3689 | 0.7870 | 0.7878 | |
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| 0.4135 | 8.0 | 4216 | 0.7778 | 0.8016 | |
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| 0.3376 | 9.0 | 4743 | 0.8673 | 0.7993 | |
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| 0.2972 | 10.0 | 5270 | 0.8790 | 0.7901 | |
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| 0.2734 | 11.0 | 5797 | 0.9525 | 0.7913 | |
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| 0.2569 | 12.0 | 6324 | 0.9557 | 0.7936 | |
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| 0.2431 | 13.0 | 6851 | 0.9595 | 0.7878 | |
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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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