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README.md
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---
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license: mit
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base_model: gpt2
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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: gmra_model_gpt2_14082023T103028
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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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# gmra_model_gpt2_14082023T103028
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2685
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- Accuracy: 0.9192
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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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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| No log | 1.0 | 71 | 0.6906 | 0.7742 |
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| No log | 1.99 | 142 | 0.4773 | 0.8286 |
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| No log | 2.99 | 213 | 0.3916 | 0.8708 |
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| No log | 4.0 | 285 | 0.3393 | 0.8849 |
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| No log | 5.0 | 356 | 0.3144 | 0.9007 |
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| No log | 5.99 | 427 | 0.2959 | 0.9112 |
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| No log | 6.99 | 498 | 0.2825 | 0.9165 |
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| 0.538 | 8.0 | 570 | 0.2803 | 0.9069 |
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| 0.538 | 9.0 | 641 | 0.2612 | 0.9192 |
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| 0.538 | 9.96 | 710 | 0.2685 | 0.9192 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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