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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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