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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gpt-regular-test |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gpt-regular-test |
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i was stupid and all the newline tokens are replaced with [/n] so be wary if you're using the demo on this page that that just means new line |
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```python |
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from transformers import AutoTokenizer |
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from transformers import AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained("crumb/gpt2-regular-large") |
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tokenizer = AutoTokenizer.from_pretrained("gpt2-large", use_fast=True) |
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prompt = """(Episode begins with Mordecai and Rigby watching TV) |
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Mordecai: Dude, what are you doing? I think I'm gonna lose my mind. |
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Rigby:""" |
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prompt=prompt.replace("\n","[/n]") |
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tokenz = tokenizer(prompt,return_tensors='pt')['input_ids'] |
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output = model.generate( |
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tokenz, |
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max_length=length, |
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num_return_sequences=1, |
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top_p=.92, |
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temperature=.65, |
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do_sample=True, |
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top_k=125, |
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early_stopping=True, |
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pad_token_id=tokenizer.eos_token_id |
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) |
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output = tokenizer.decode(output[0]).replace("[/n]","\n") |
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print(output) |
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``` |
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This model is a fine-tuned version of gpt2-large on the entirety of Regular Show. It achieves the following results on the evaluation set (The Power, Death Punchies, Do Me a Solid): |
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- Loss: 1.6383 |
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## Intended uses & limitations |
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Same as gpt2-large |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.1844 | 1.0 | 7633 | 1.6383 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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