New model from https://wandb.ai/wandb/huggingtweets/runs/6ywcmhlx
Browse files- README.md +8 -8
- pytorch_model.bin +2 -2
- training_args.bin +1 -1
README.md
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---
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language: en
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thumbnail: https://
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tags:
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- huggingtweets
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widget:
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<tbody style='border-width:0'>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Tweets downloaded</td>
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<td style='border-width:0'>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Retweets</td>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Short tweets</td>
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<td style='border-width:0'>
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</tr>
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<tr style='border-width:0'>
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<td style='border-width:0'>Tweets kept</td>
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</tr>
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</tbody>
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</table>
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[Explore the data](https://wandb.ai/wandb/huggingtweets/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 @marknorm's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/
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## Intended uses & limitations
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[](https://github.com/borisdayma/huggingtweets)
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<!--- random size file
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---
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language: en
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thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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tags:
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- huggingtweets
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widget:
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<tbody style='border-width:0'>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Tweets downloaded</td>
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<td style='border-width:0'>3212</td>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Retweets</td>
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</tr>
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<tr style='border-width:0 0 1px 0; border-color: #E2E8F0'>
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<td style='border-width:0'>Short tweets</td>
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<td style='border-width:0'>591</td>
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</tr>
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<tr style='border-width:0'>
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<td style='border-width:0'>Tweets kept</td>
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<td style='border-width:0'>2459</td>
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</tr>
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</tbody>
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</table>
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1k5cic9q/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 @marknorm's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/6ywcmhlx) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/6ywcmhlx/artifacts) is logged and versioned.
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## Intended uses & limitations
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[](https://github.com/borisdayma/huggingtweets)
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pytorch_model.bin
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training_args.bin
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