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				| @ -30,6 +30,7 @@ Validation set length: 55 | ||||
| Test set length: 110 | ||||
| -------------------------------------------------- | ||||
| Device: cpu | ||||
| -------------------------------------------------- | ||||
| File already exists and is up-to-date: gpt2/355M/checkpoint | ||||
| File already exists and is up-to-date: gpt2/355M/encoder.json | ||||
| File already exists and is up-to-date: gpt2/355M/hparams.json | ||||
| @ -50,7 +51,7 @@ Training completed in 15.66 minutes. | ||||
| Plot saved as loss-plot-standalone.pdf | ||||
| -------------------------------------------------- | ||||
| Generating responses | ||||
| 100%|██████████████████████████████████████████████████████████████████████████| 110/110 [06:57<00:00,  3.80s/it] | ||||
| 100%|█████████████████████████████████████████████████████████| 110/110 [06:57<00:00,  3.80s/it] | ||||
| Responses saved as instruction-data-with-response-standalone.json | ||||
| Model saved as gpt2-medium355M-sft-standalone.pth | ||||
| ``` | ||||
|  | ||||
| @ -185,6 +185,8 @@ def main(): | ||||
|     tokenizer = tiktoken.get_encoding("gpt2") | ||||
|     device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | ||||
|     print("Device:", device) | ||||
|     print(50*"-") | ||||
| 
 | ||||
|     customized_collate_fn = partial(custom_collate_fn, device=device, allowed_max_length=1024) | ||||
| 
 | ||||
|     num_workers = 0 | ||||
|  | ||||
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