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update model card 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: switchboard-rarity-seed
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+ results: []
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+ ---
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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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+
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+ # switchboard-rarity-seed
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+
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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: 4.0985
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 6
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 6.3581 | 0.29 | 500 | 5.3466 |
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+ | 5.0332 | 0.58 | 1000 | 4.9336 |
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+ | 4.7065 | 0.87 | 1500 | 4.6924 |
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+ | 4.4439 | 1.17 | 2000 | 4.5465 |
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+ | 4.2929 | 1.46 | 2500 | 4.4328 |
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+ | 4.1869 | 1.75 | 3000 | 4.3248 |
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+ | 4.0802 | 2.04 | 3500 | 4.2481 |
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+ | 3.8877 | 2.33 | 4000 | 4.2060 |
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+ | 3.8547 | 2.62 | 4500 | 4.1542 |
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+ | 3.83 | 2.92 | 5000 | 4.0982 |
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+ | 3.6375 | 3.21 | 5500 | 4.0946 |
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+ | 3.5896 | 3.5 | 6000 | 4.0648 |
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+ | 3.5596 | 3.79 | 6500 | 4.0309 |
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+ | 3.474 | 4.08 | 7000 | 4.0282 |
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+ | 3.3101 | 4.37 | 7500 | 4.0247 |
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+ | 3.3055 | 4.66 | 8000 | 4.0122 |
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+ | 3.2891 | 4.96 | 8500 | 3.9981 |
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+ | 3.1562 | 5.25 | 9000 | 4.0102 |
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+ | 3.1289 | 5.54 | 9500 | 4.0093 |
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+ | 3.1216 | 5.83 | 10000 | 4.0085 |
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+
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+
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+ ### Framework versions
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+
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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