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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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- f1
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model-index:
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- name: mobilebert_add_GLUE_Experiment_mrpc_256
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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: mrpc
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split: validation
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args: mrpc
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6813725490196079
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- name: F1
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type: f1
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value: 0.8104956268221574
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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_mrpc_256
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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: 0.6733
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- Accuracy: 0.6814
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- F1: 0.8105
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- Combined Score: 0.7459
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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 | F1 | Combined Score |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
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| 0.6419 | 1.0 | 29 | 0.6266 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6297 | 2.0 | 58 | 0.6236 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6307 | 3.0 | 87 | 0.6241 | 0.6838 | 0.8122 | 0.7480 |
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| 0.63 | 4.0 | 116 | 0.6243 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6283 | 5.0 | 145 | 0.6219 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6243 | 6.0 | 174 | 0.6207 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6206 | 7.0 | 203 | 0.6346 | 0.6838 | 0.8122 | 0.7480 |
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| 0.6034 | 8.0 | 232 | 0.6519 | 0.6348 | 0.7545 | 0.6947 |
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| 0.5877 | 9.0 | 261 | 0.6375 | 0.6838 | 0.8122 | 0.7480 |
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| 0.5722 | 10.0 | 290 | 0.6446 | 0.6299 | 0.7504 | 0.6902 |
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| 0.5619 | 11.0 | 319 | 0.6733 | 0.6814 | 0.8105 | 0.7459 |
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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 2.8.0
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- Tokenizers 0.13.2
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