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New model from https://wandb.ai/wandb/huggingtweets/runs/2wqm0qaq

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Files changed (3) hide show
  1. README.md +8 -8
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
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/elonmusk/1612607592822/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 [@elonmusk's tweets](https://twitter.com/elonmusk).
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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'>3239</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'>213</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'>809</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'>2217</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/39fqhbin/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 @elonmusk's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/22iuzhao) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/22iuzhao/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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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'>3210</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'>207</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'>802</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'>2201</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/1lxqsday/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 @elonmusk's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2wqm0qaq) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2wqm0qaq/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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