boris commited on
Commit
efb8095
1 Parent(s): 623ae1e

New model from https://wandb.ai/wandb/huggingtweets/runs/199ych58

Browse files
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  language: en
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- thumbnail: https://www.huggingtweets.com/marknorm/1606324101714/predictions.png
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  tags:
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  - huggingtweets
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  widget:
@@ -51,32 +51,32 @@ The model was trained on [@marknorm's tweets](https://twitter.com/marknorm).
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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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- <td style='border-width:0'>162</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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@@ -110,4 +110,4 @@ For more details, visit the project repository.
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  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](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'>3208</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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+ <td style='border-width:0'>166</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'>582</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'>2460</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/c7f7hyql/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/199ych58) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/199ych58/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
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+ <!--- random size file -->
config.json CHANGED
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