AlekseyKorshuk
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huggingartists
Browse files- README.md +3 -3
- evaluation.txt +1 -1
- tokenizer_config.json +1 -1
README.md
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dataset = load_dataset("huggingartists/madonna")
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```
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[Explore the data](https://wandb.ai/huggingartists/huggingartists/runs/
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## Training procedure
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The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on Madonna's lyrics.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/huggingartists/huggingartists/runs/
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At the end of training, [the final model](https://wandb.ai/huggingartists/huggingartists/runs/
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## How to use
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dataset = load_dataset("huggingartists/madonna")
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```
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[Explore the data](https://wandb.ai/huggingartists/huggingartists/runs/2eqc1vv3/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
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## Training procedure
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The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on Madonna's lyrics.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/huggingartists/huggingartists/runs/ppm2eyoj) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/huggingartists/huggingartists/runs/ppm2eyoj/artifacts) is logged and versioned.
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## How to use
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evaluation.txt
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{"eval_loss":
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{"eval_loss": 3.1591076850891113, "eval_runtime": 3.3487, "eval_samples_per_second": 21.202, "eval_steps_per_second": 2.688, "epoch": 1.0}
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tokenizer_config.json
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "huggingartists/zemfira", "tokenizer_class": "GPT2Tokenizer"}
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