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New model from https://wandb.ai/wandb/huggingtweets/runs/2wwe80fw

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Files changed (5) hide show
  1. README.md +24 -14
  2. config.json +2 -1
  3. pytorch_model.bin +1 -1
  4. tokenizer.json +0 -0
  5. training_args.bin +2 -2
README.md CHANGED
@@ -1,17 +1,27 @@
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  ---
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  language: en
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- thumbnail: https://www.huggingtweets.com/drsweety303/1619833945455/predictions.png
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  tags:
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  - huggingtweets
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  widget:
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  - text: "My dream is"
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  ---
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- <div>
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- <div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1377788200199065611/vkwcelvm_400x400.jpg')">
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- </div>
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- <div style="margin-top: 8px; font-size: 19px; font-weight: 800">Dr. Roberta Bobby 🤖 AI Bot </div>
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- <div style="font-size: 15px">@drsweety303 bot</div>
 
 
 
 
 
 
 
 
 
 
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  </div>
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  I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
@@ -28,24 +38,24 @@ To understand how the model was developed, check the [W&B report](https://wandb.
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  ## Training data
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- The model was trained on [@drsweety303's tweets](https://twitter.com/drsweety303).
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- | Data | Quantity |
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  | --- | --- |
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  | Tweets downloaded | 3241 |
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- | Retweets | 280 |
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- | Short tweets | 270 |
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- | Tweets kept | 2691 |
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- [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3j2hydsl/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 @drsweety303's tweets.
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- Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/334u5jre) for full transparency and reproducibility.
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- At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/334u5jre/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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  - text: "My dream is"
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  ---
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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/1377788200199065611/vkwcelvm_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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+ </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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+ </div>
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+ </div>
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+ <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI BOT 🤖</div>
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+ <div style="text-align: center; font-size: 16px; font-weight: 800">Dr. Roberta Bobby</div>
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+ <div style="text-align: center; font-size: 14px;">@drsweety303</div>
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  </div>
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  I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
 
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  ## Training data
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+ The model was trained on tweets from Dr. Roberta Bobby.
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+ | Data | Dr. Roberta Bobby |
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  | --- | --- |
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  | Tweets downloaded | 3241 |
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+ | Retweets | 291 |
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+ | Short tweets | 285 |
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+ | Tweets kept | 2665 |
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+ [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/39xsuhxd/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 @drsweety303's tweets.
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+ Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2wwe80fw) for full transparency and reproducibility.
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+ At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2wwe80fw/artifacts) is logged and versioned.
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  ## How to use
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config.json CHANGED
@@ -19,6 +19,7 @@
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  "n_layer": 12,
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  "n_positions": 1024,
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  "resid_pdrop": 0.1,
 
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  "summary_activation": null,
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  "summary_first_dropout": 0.1,
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  "summary_proj_to_labels": true,
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  "top_p": 0.95
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  }
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  },
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- "transformers_version": "4.5.1",
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  "use_cache": true,
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  "vocab_size": 50257
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  }
 
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  "n_layer": 12,
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  "n_positions": 1024,
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  "resid_pdrop": 0.1,
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+ "scale_attn_weights": true,
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  "summary_activation": null,
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  "summary_first_dropout": 0.1,
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  "summary_proj_to_labels": true,
 
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  "top_p": 0.95
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  }
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  },
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+ "transformers_version": "4.6.0",
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  "use_cache": true,
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  "vocab_size": 50257
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  }
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