New model from https://wandb.ai/wandb/huggingtweets/runs/5uf3iuhw
Browse files- README.md +3 -3
- config.json +6 -4
- pytorch_model.bin +2 -2
- training_args.bin +1 -1
README.md
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@@ -47,15 +47,15 @@ The model was trained on tweets from Vaush.
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| Short tweets | 357 |
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| Tweets kept | 1956 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/
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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 @vaushv's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/
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## How to use
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| Short tweets | 357 |
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| Tweets kept | 1956 |
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[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/kae7zvq9/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 @vaushv's tweets.
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Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/5uf3iuhw) for full transparency and reproducibility.
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At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/5uf3iuhw/artifacts) is logged and versioned.
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## How to use
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config.json
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{
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"_name_or_path": "gpt2",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd":
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"n_head":
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"n_inner": null,
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"n_layer":
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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{
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"_name_or_path": "gpt2-medium",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 1024,
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"n_head": 16,
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"n_inner": null,
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"n_layer": 24,
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"n_positions": 1024,
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"n_special": 0,
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"predict_special_tokens": true,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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pytorch_model.bin
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size
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size 1444569373
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training_args.bin
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size 3579
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