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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: olm-bert-tiny-december-2022-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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# olm-bert-tiny-december-2022-target-glue-qnli
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This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6358
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- Accuracy: 0.6306
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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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- training_steps: 5000
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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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| 0.692 | 0.15 | 500 | 0.6882 | 0.5574 |
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| 0.6777 | 0.31 | 1000 | 0.6637 | 0.6059 |
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| 0.667 | 0.46 | 1500 | 0.6568 | 0.6064 |
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| 0.6609 | 0.61 | 2000 | 0.6517 | 0.6193 |
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| 0.6596 | 0.76 | 2500 | 0.6514 | 0.6127 |
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| 0.6584 | 0.92 | 3000 | 0.6496 | 0.6202 |
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| 0.6514 | 1.07 | 3500 | 0.6487 | 0.6191 |
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| 0.652 | 1.22 | 4000 | 0.6420 | 0.6253 |
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| 0.6449 | 1.37 | 4500 | 0.6415 | 0.6268 |
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| 0.6477 | 1.53 | 5000 | 0.6358 | 0.6306 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.1.dev0
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- Tokenizers 0.13.2
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