New model from https://wandb.ai/wandb/huggingtweets/runs/uheep0ve

README.md

@@ -42,20 +42,20 @@ The model was trained on tweets from Emmark.
 
 | Data | Emmark |
 | --- | --- |
-| Tweets downloaded | 3250 |
-| Retweets | 123 |
-| Short tweets | 2147 |
-| Tweets kept | 980 |
+| Tweets downloaded | 3249 |
+| Retweets | 200 |
+| Short tweets | 2112 |
+| Tweets kept | 937 |
 
-[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/xm8a605r/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
+[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/zjdekgzp/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
 
 ## Training procedure
 
 The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @emmarkgadgets's tweets.
 
-Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/vgfewo88) for full transparency and reproducibility.
+Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/uheep0ve) for full transparency and reproducibility.
 
-At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/vgfewo88/artifacts) is logged and versioned.
+At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/uheep0ve/artifacts) is logged and versioned.
 
 ## How to use
 

config.json

@@ -37,7 +37,7 @@
     }
   },
   "torch_dtype": "float32",
-  "transformers_version": "4.22.2",
+  "transformers_version": "4.23.1",
   "use_cache": true,
   "vocab_size": 50257
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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 size 510396521

training_args.bin

@@ -1,3 +1,3 @@
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 size 3375