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Model: toloka/gpt2-large-supervised-prompt-writing Source: Original Platform
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README.md
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README.md
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license: mit
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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: gpt2-sweep
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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-sweep
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This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0808
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- Accuracy: 0.8556
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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: 2.294477077303931e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 2.0
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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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| 2.4827 | 0.19 | 1000 | 2.4565 | 0.8520 |
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| 2.6468 | 0.37 | 2000 | 2.3303 | 0.8530 |
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| 2.5106 | 0.56 | 3000 | 2.2487 | 0.8537 |
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| 2.0732 | 0.74 | 4000 | 2.2020 | 0.8541 |
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| 2.159 | 0.93 | 5000 | 2.1594 | 0.8545 |
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| 1.856 | 1.12 | 6000 | 2.1518 | 0.8548 |
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| 1.9138 | 1.3 | 7000 | 2.1261 | 0.8551 |
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| 1.8055 | 1.49 | 8000 | 2.1126 | 0.8552 |
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| 2.0385 | 1.67 | 9000 | 2.1008 | 0.8554 |
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| 1.9648 | 1.86 | 10000 | 2.0858 | 0.8555 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 2.0.0+cu117
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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