boris commited on
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New model from https://wandb.ai/wandb/huggingtweets/runs/9dh3r8n9

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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: http://www.huggingtweets.com/newscollected/1650765206350/predictions.png
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  tags:
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  - huggingtweets
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  widget:
@@ -10,7 +10,7 @@ widget:
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  <div class="inline-flex flex-col" style="line-height: 1.5;">
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  <div class="flex">
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  <div
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- style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1480040272524419077/IBXoeelJ_400x400.jpg&#39;)">
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  </div>
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  <div
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  style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
@@ -42,20 +42,20 @@ The model was trained on tweets from del co.
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  | Data | del co |
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  | --- | --- |
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- | Tweets downloaded | 343 |
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  | Retweets | 30 |
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- | Short tweets | 63 |
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- | Tweets kept | 250 |
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- [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1z9h8ysl/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 @newscollected's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1iqirrwi) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1iqirrwi/artifacts) is logged and versioned.
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  ## How to use
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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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  <div class="inline-flex flex-col" style="line-height: 1.5;">
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  <div class="flex">
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  <div
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+ style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1522032150358511616/83U7w6rG_400x400.jpg&#39;)">
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  </div>
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  <div
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  style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)">
 
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  | Data | del co |
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  | --- | --- |
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+ | Tweets downloaded | 355 |
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  | Retweets | 30 |
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+ | Short tweets | 67 |
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+ | Tweets kept | 258 |
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+ [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/s6lqhaxq/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 @newscollected's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/9dh3r8n9) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/9dh3r8n9/artifacts) is logged and versioned.
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  ## How to use
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