boris commited on
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New model from https://wandb.ai/wandb/huggingtweets/runs/3t9hyz6q

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Files changed (3) hide show
  1. README.md +8 -8
  2. pytorch_model.bin +2 -2
  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/idph/1608314896334/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 [@idph's tweets](https://twitter.com/idph).
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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'>3240</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'>685</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'>38</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'>2517</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/1igarih0/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 @idph's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/bliwsl3m) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/bliwsl3m/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'>3197</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'>686</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'>39</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'>2472</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/f4tytzld/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 @idph's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3t9hyz6q) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3t9hyz6q/artifacts) is logged and versioned.
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  ## Intended uses & limitations
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