2024-06-01 14:49 - Cuda check 2024-06-01 14:49 - True 2024-06-01 14:49 - 2 2024-06-01 14:49 - Configue Model and tokenizer 2024-06-01 14:49 - Cuda check 2024-06-01 14:49 - True 2024-06-01 14:49 - 2 2024-06-01 14:49 - Configue Model and tokenizer 2024-06-01 14:49 - Memory usage in 0.00 GB 2024-06-01 14:49 - Memory usage in 0.00 GB 2024-06-01 14:49 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 14:49 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 14:49 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 14:49 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 14:49 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 14:49 - Setup PEFT 2024-06-01 14:49 - Setup optimizer 2024-06-01 14:49 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 14:49 - Setup PEFT 2024-06-01 14:49 - Setup optimizer 2024-06-01 14:49 - Start training!! 2024-06-01 14:49 - Start training!! 2024-06-01 14:51 - Cuda check 2024-06-01 14:51 - True 2024-06-01 14:51 - 2 2024-06-01 14:51 - Configue Model and tokenizer 2024-06-01 14:51 - Cuda check 2024-06-01 14:51 - True 2024-06-01 14:51 - 2 2024-06-01 14:51 - Configue Model and tokenizer 2024-06-01 14:51 - Memory usage in 0.00 GB 2024-06-01 14:51 - Memory usage in 0.00 GB 2024-06-01 14:51 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 14:51 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 14:51 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 14:51 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 14:51 - Setup PEFT 2024-06-01 14:51 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 14:51 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 14:51 - Setup PEFT 2024-06-01 14:51 - Setup optimizer 2024-06-01 14:51 - Setup optimizer 2024-06-01 14:51 - Start training!! 2024-06-01 14:51 - Start training!! 2024-06-01 15:49 - Training complete!!! 2024-06-01 15:49 - Training complete!!! 2024-06-01 20:49 - Cuda check 2024-06-01 20:49 - True 2024-06-01 20:49 - 2 2024-06-01 20:49 - Configue Model and tokenizer 2024-06-01 20:49 - Cuda check 2024-06-01 20:49 - True 2024-06-01 20:49 - 2 2024-06-01 20:49 - Configue Model and tokenizer 2024-06-01 20:49 - Memory usage in 0.00 GB 2024-06-01 20:49 - Memory usage in 0.00 GB 2024-06-01 20:49 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:49 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:49 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:49 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:49 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:49 - Setup PEFT 2024-06-01 20:49 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:49 - Setup PEFT 2024-06-01 20:49 - Setup optimizer 2024-06-01 20:49 - Setup optimizer 2024-06-01 20:49 - Start training!! 2024-06-01 20:49 - Start training!! 2024-06-01 20:55 - Cuda check 2024-06-01 20:55 - True 2024-06-01 20:55 - 2 2024-06-01 20:55 - Configue Model and tokenizer 2024-06-01 20:55 - Cuda check 2024-06-01 20:55 - True 2024-06-01 20:55 - 2 2024-06-01 20:55 - Configue Model and tokenizer 2024-06-01 20:55 - Memory usage in 0.00 GB 2024-06-01 20:55 - Memory usage in 0.00 GB 2024-06-01 20:55 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:55 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:55 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:55 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:55 - Setup PEFT 2024-06-01 20:55 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:55 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:55 - Setup PEFT 2024-06-01 20:55 - Setup optimizer 2024-06-01 20:55 - Setup optimizer 2024-06-01 20:55 - Continue training!! 2024-06-01 20:55 - Continue training!! 2024-06-01 20:56 - Training complete!!! 2024-06-01 20:56 - Training complete!!! 2024-06-01 20:58 - Cuda check 2024-06-01 20:58 - True 2024-06-01 20:58 - 2 2024-06-01 20:58 - Configue Model and tokenizer 2024-06-01 20:58 - Cuda check 2024-06-01 20:58 - True 2024-06-01 20:58 - 2 2024-06-01 20:58 - Configue Model and tokenizer 2024-06-01 20:58 - Memory usage in 0.00 GB 2024-06-01 20:58 - Memory usage in 0.00 GB 2024-06-01 20:58 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:58 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:58 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:58 - Setup PEFT 2024-06-01 20:58 - Setup optimizer 2024-06-01 20:58 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 20:58 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 20:58 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 20:58 - Setup PEFT 2024-06-01 20:58 - Setup optimizer 2024-06-01 20:58 - Continue training!! 2024-06-01 20:58 - Continue training!! 2024-06-01 20:59 - Training complete!!! 2024-06-01 20:59 - Training complete!!! 2024-06-01 21:04 - Cuda check 2024-06-01 21:04 - True 2024-06-01 21:04 - 2 2024-06-01 21:04 - Configue Model and tokenizer 2024-06-01 21:04 - Cuda check 2024-06-01 21:04 - True 2024-06-01 21:04 - 2 2024-06-01 21:04 - Configue Model and tokenizer 2024-06-01 21:04 - Memory usage in 0.00 GB 2024-06-01 21:04 - Memory usage in 0.00 GB 2024-06-01 21:04 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 21:04 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:04 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:04 - Setup PEFT 2024-06-01 21:04 - Setup optimizer 2024-06-01 21:04 - Dataset loaded successfully: train-Jingmei/Pandemic_Wiki test -Jingmei/Pandemic 2024-06-01 21:04 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 2152 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:04 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 24863 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:04 - Setup PEFT 2024-06-01 21:04 - Setup optimizer 2024-06-01 21:05 - Continue training!! 2024-06-01 21:05 - Continue training!! 2024-06-01 21:05 - Training complete!!! 2024-06-01 21:05 - Training complete!!! 2024-06-01 21:07 - Cuda check 2024-06-01 21:07 - True 2024-06-01 21:07 - 2 2024-06-01 21:07 - Configue Model and tokenizer 2024-06-01 21:07 - Cuda check 2024-06-01 21:07 - True 2024-06-01 21:07 - 2 2024-06-01 21:07 - Configue Model and tokenizer 2024-06-01 21:07 - Memory usage in 0.00 GB 2024-06-01 21:07 - Memory usage in 0.00 GB 2024-06-01 21:07 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:07 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:07 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:07 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:07 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:07 - Setup PEFT 2024-06-01 21:07 - Setup optimizer 2024-06-01 21:07 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:07 - Setup PEFT 2024-06-01 21:07 - Setup optimizer 2024-06-01 21:07 - Continue training!! 2024-06-01 21:07 - Continue training!! 2024-06-01 21:08 - Training complete!!! 2024-06-01 21:08 - Training complete!!! 2024-06-01 21:09 - Cuda check 2024-06-01 21:09 - True 2024-06-01 21:09 - 2 2024-06-01 21:09 - Configue Model and tokenizer 2024-06-01 21:09 - Cuda check 2024-06-01 21:09 - True 2024-06-01 21:09 - 2 2024-06-01 21:09 - Configue Model and tokenizer 2024-06-01 21:09 - Memory usage in 0.00 GB 2024-06-01 21:09 - Memory usage in 0.00 GB 2024-06-01 21:09 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:09 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:09 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:09 - Setup PEFT 2024-06-01 21:09 - Setup optimizer 2024-06-01 21:09 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:09 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:09 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:09 - Setup PEFT 2024-06-01 21:09 - Setup optimizer 2024-06-01 21:09 - Continue training!! 2024-06-01 21:09 - Continue training!! 2024-06-01 21:19 - Training complete!!! 2024-06-01 21:19 - Training complete!!! 2024-06-01 21:20 - Cuda check 2024-06-01 21:20 - True 2024-06-01 21:20 - 2 2024-06-01 21:20 - Configue Model and tokenizer 2024-06-01 21:20 - Cuda check 2024-06-01 21:20 - True 2024-06-01 21:20 - 2 2024-06-01 21:20 - Configue Model and tokenizer 2024-06-01 21:20 - Memory usage in 0.00 GB 2024-06-01 21:20 - Memory usage in 0.00 GB 2024-06-01 21:20 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:20 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:20 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:20 - Setup PEFT 2024-06-01 21:20 - Dataset loaded successfully: train-Jingmei/Pandemic_ACDC test -Jingmei/Pandemic 2024-06-01 21:20 - Tokenize data: DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 625 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 8264 }) }) 2024-06-01 21:20 - Split data into chunks:DatasetDict({ train: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 3938 }) test: Dataset({ features: ['input_ids', 'attention_mask'], num_rows: 198964 }) }) 2024-06-01 21:20 - Setup PEFT 2024-06-01 21:20 - Setup optimizer 2024-06-01 21:20 - Setup optimizer 2024-06-01 21:20 - Continue training!! 2024-06-01 21:20 - Continue training!! 2024-06-01 21:21 - Training complete!!!