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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- generator
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model-index:
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- name: gpt2-concat-cbt-rarity-2k-p3k-rerun
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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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# gpt2-concat-cbt-rarity-2k-p3k-rerun
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.0111
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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: 0.0005
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- train_batch_size: 64
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- eval_batch_size: 64
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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: cosine
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 7
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 6.7193 | 0.29 | 500 | 5.6348 |
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| 5.3717 | 0.58 | 1000 | 5.2023 |
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| 5.0316 | 0.87 | 1500 | 4.9479 |
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| 4.7526 | 1.17 | 2000 | 4.8054 |
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| 4.5908 | 1.46 | 2500 | 4.6881 |
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| 4.4855 | 1.75 | 3000 | 4.5743 |
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| 4.37 | 2.04 | 3500 | 4.4982 |
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| 4.1665 | 2.33 | 4000 | 4.4536 |
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| 4.1433 | 2.62 | 4500 | 4.3994 |
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| 4.1049 | 2.91 | 5000 | 4.3436 |
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| 3.9129 | 3.21 | 5500 | 4.3424 |
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| 3.8605 | 3.5 | 6000 | 4.3136 |
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| 3.8444 | 3.79 | 6500 | 4.2788 |
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| 3.7551 | 4.08 | 7000 | 4.2807 |
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| 3.5722 | 4.37 | 7500 | 4.2752 |
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| 3.58 | 4.66 | 8000 | 4.2599 |
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| 3.5691 | 4.95 | 8500 | 4.2378 |
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| 3.3607 | 5.24 | 9000 | 4.2659 |
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| 3.3218 | 5.54 | 9500 | 4.2623 |
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| 3.3249 | 5.83 | 10000 | 4.2549 |
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| 3.2621 | 6.12 | 10500 | 4.2656 |
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| 3.1746 | 6.41 | 11000 | 4.2682 |
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| 3.1689 | 6.7 | 11500 | 4.2679 |
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| 3.17 | 6.99 | 12000 | 4.2677 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.13.0
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- Tokenizers 0.13.3
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