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--- |
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license: mit |
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base_model: gpt2-medium |
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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-medium_15082023T113143 |
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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-medium_15082023T113143 |
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This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2694 |
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- Accuracy: 0.9464 |
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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 | 142 | 0.4750 | 0.8409 | |
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| No log | 2.0 | 284 | 0.2932 | 0.9033 | |
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| No log | 2.99 | 426 | 0.2850 | 0.9192 | |
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| 0.5761 | 4.0 | 569 | 0.2622 | 0.9279 | |
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| 0.5761 | 5.0 | 711 | 0.2580 | 0.9367 | |
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| 0.5761 | 6.0 | 853 | 0.2768 | 0.9394 | |
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| 0.5761 | 6.99 | 995 | 0.2640 | 0.9473 | |
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| 0.0682 | 8.0 | 1138 | 0.2493 | 0.9464 | |
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| 0.0682 | 9.0 | 1280 | 0.2739 | 0.9446 | |
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| 0.0682 | 9.98 | 1420 | 0.2694 | 0.9464 | |
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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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