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update model card README.md

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+ ---
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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_sst2_128
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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: 0.7947247706422018
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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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+ # mobilebert_add_GLUE_Experiment_sst2_128
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+
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+ This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5943
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+ - Accuracy: 0.7947
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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: 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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+
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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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+ | 0.6677 | 1.0 | 527 | 0.6771 | 0.5757 |
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+ | 0.5966 | 2.0 | 1054 | 0.7135 | 0.5424 |
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+ | 0.5714 | 3.0 | 1581 | 0.7271 | 0.5550 |
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+ | 0.5573 | 4.0 | 2108 | 0.6892 | 0.5619 |
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+ | 0.501 | 5.0 | 2635 | 0.4546 | 0.7798 |
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+ | 0.2856 | 6.0 | 3162 | 0.4613 | 0.8050 |
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+ | 0.2288 | 7.0 | 3689 | 0.4543 | 0.7982 |
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+ | 0.2027 | 8.0 | 4216 | 0.4662 | 0.7993 |
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+ | 0.1883 | 9.0 | 4743 | 0.5168 | 0.8039 |
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+ | 0.1779 | 10.0 | 5270 | 0.5748 | 0.7856 |
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+ | 0.1691 | 11.0 | 5797 | 0.5196 | 0.8028 |
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+ | 0.1596 | 12.0 | 6324 | 0.5943 | 0.7947 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.8.0
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+ - Tokenizers 0.13.2