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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-sst2
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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-sst2
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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: 0.4126
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- Accuracy: 0.8280
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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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| 0.5968 | 0.24 | 500 | 0.4910 | 0.7718 |
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| 0.4845 | 0.48 | 1000 | 0.4722 | 0.7810 |
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| 0.4455 | 0.71 | 1500 | 0.4468 | 0.7924 |
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| 0.4397 | 0.95 | 2000 | 0.4488 | 0.7901 |
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| 0.4028 | 1.19 | 2500 | 0.4262 | 0.8119 |
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| 0.3898 | 1.43 | 3000 | 0.4375 | 0.7936 |
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| 0.3768 | 1.66 | 3500 | 0.4207 | 0.8050 |
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| 0.3725 | 1.9 | 4000 | 0.4228 | 0.8245 |
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| 0.3515 | 2.14 | 4500 | 0.4336 | 0.8085 |
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| 0.3326 | 2.38 | 5000 | 0.4126 | 0.8280 |
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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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