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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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- f1 |
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model-index: |
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- name: olm-bert-tiny-december-2022-target-glue-qqp |
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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-qqp |
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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: 0.5217 |
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- Accuracy: 0.7433 |
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- F1: 0.6048 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.6283 | 0.04 | 500 | 0.5955 | 0.6795 | 0.5186 | |
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| 0.5875 | 0.09 | 1000 | 0.5763 | 0.6972 | 0.5596 | |
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| 0.5791 | 0.13 | 1500 | 0.5690 | 0.6975 | 0.6011 | |
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| 0.5666 | 0.18 | 2000 | 0.5536 | 0.7156 | 0.5520 | |
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| 0.5568 | 0.22 | 2500 | 0.5447 | 0.7230 | 0.5709 | |
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| 0.5489 | 0.26 | 3000 | 0.5386 | 0.7281 | 0.5665 | |
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| 0.5465 | 0.31 | 3500 | 0.5305 | 0.7329 | 0.5917 | |
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| 0.5384 | 0.35 | 4000 | 0.5262 | 0.7357 | 0.6231 | |
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| 0.5422 | 0.4 | 4500 | 0.5207 | 0.7409 | 0.6200 | |
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| 0.5299 | 0.44 | 5000 | 0.5217 | 0.7433 | 0.6048 | |
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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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