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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_sa_GLUE_Experiment_logit_kd_mnli_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: mnli
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split: validation_matched
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args: mnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6026490066225165
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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_sa_GLUE_Experiment_logit_kd_mnli_128
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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: 1.3296
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- Accuracy: 0.6026
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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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| 1.6825 | 1.0 | 3068 | 1.4581 | 0.5256 |
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| 1.4941 | 2.0 | 6136 | 1.3516 | 0.5680 |
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| 1.4199 | 3.0 | 9204 | 1.3259 | 0.5712 |
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| 1.3747 | 4.0 | 12272 | 1.3024 | 0.5856 |
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| 1.34 | 5.0 | 15340 | 1.2875 | 0.5931 |
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| 1.3087 | 6.0 | 18408 | 1.2730 | 0.5928 |
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| 1.2769 | 7.0 | 21476 | 1.2845 | 0.5916 |
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| 1.246 | 8.0 | 24544 | 1.2750 | 0.5965 |
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| 1.2166 | 9.0 | 27612 | 1.2651 | 0.6020 |
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| 1.1883 | 10.0 | 30680 | 1.2773 | 0.6043 |
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| 1.1604 | 11.0 | 33748 | 1.2555 | 0.6011 |
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| 1.1329 | 12.0 | 36816 | 1.2792 | 0.5991 |
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| 1.1074 | 13.0 | 39884 | 1.2891 | 0.5986 |
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| 1.0812 | 14.0 | 42952 | 1.2889 | 0.5947 |
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| 1.0577 | 15.0 | 46020 | 1.2871 | 0.5970 |
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| 1.0338 | 16.0 | 49088 | 1.3296 | 0.6026 |
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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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