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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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metrics:
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- accuracy
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model-index:
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- name: tiny-vanilla-target-glue-qnli
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results: []
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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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# tiny-vanilla-target-glue-qnli
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4624
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- Accuracy: 0.7825
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant
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- num_epochs: 200
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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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| 0.6082 | 0.15 | 500 | 0.5375 | 0.7362 |
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| 0.5378 | 0.31 | 1000 | 0.5192 | 0.7459 |
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| 0.5161 | 0.46 | 1500 | 0.4967 | 0.7672 |
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| 0.5097 | 0.61 | 2000 | 0.5182 | 0.7505 |
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| 0.5092 | 0.76 | 2500 | 0.4728 | 0.7750 |
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| 0.5011 | 0.92 | 3000 | 0.4660 | 0.7866 |
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| 0.4889 | 1.07 | 3500 | 0.4476 | 0.7922 |
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| 0.48 | 1.22 | 4000 | 0.4619 | 0.7840 |
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| 0.4661 | 1.37 | 4500 | 0.4813 | 0.7741 |
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| 0.4742 | 1.53 | 5000 | 0.4624 | 0.7825 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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