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2024-06-01 14:49 - Cuda check |
|
2024-06-01 14:49 - True |
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2024-06-01 14:49 - 2 |
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2024-06-01 14:49 - Configue Model and tokenizer |
|
2024-06-01 14:49 - Cuda check |
|
2024-06-01 14:49 - True |
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2024-06-01 14:49 - 2 |
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2024-06-01 14:49 - Configue Model and tokenizer |
|
2024-06-01 14:49 - Memory usage in 0.00 GB |
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2024-06-01 14:49 - Memory usage in 0.00 GB |
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2024-06-01 14:49 - Dataset loaded successfully: |
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train-Jingmei/Pandemic_Wiki |
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test -Jingmei/Pandemic |
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2024-06-01 14:49 - Dataset loaded successfully: |
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train-Jingmei/Pandemic_Wiki |
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test -Jingmei/Pandemic |
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2024-06-01 14:49 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 2152 |
|
}) |
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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 |
|
}) |
|
}) |
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2024-06-01 14:49 - Setup PEFT |
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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 |
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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 |
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2024-06-01 14:51 - Memory usage in 0.00 GB |
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2024-06-01 14:51 - Dataset loaded successfully: |
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train-Jingmei/Pandemic_Wiki |
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test -Jingmei/Pandemic |
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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: |
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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 |
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2024-06-01 21:20 - Dataset loaded successfully: |
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train-Jingmei/Pandemic_ACDC |
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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!!! |
|
2024-06-01 21:21 - Training complete!!! |
|
2024-06-01 21:22 - Cuda check |
|
2024-06-01 21:22 - True |
|
2024-06-01 21:22 - 2 |
|
2024-06-01 21:22 - Configue Model and tokenizer |
|
2024-06-01 21:22 - Cuda check |
|
2024-06-01 21:22 - True |
|
2024-06-01 21:22 - 2 |
|
2024-06-01 21:22 - Configue Model and tokenizer |
|
2024-06-01 21:23 - Memory usage in 0.00 GB |
|
2024-06-01 21:23 - Memory usage in 0.00 GB |
|
2024-06-01 21:23 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_ECDC |
|
test -Jingmei/Pandemic |
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2024-06-01 21:23 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_ECDC |
|
test -Jingmei/Pandemic |
|
2024-06-01 21:23 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 7008 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-01 21:23 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 7008 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-01 21:25 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 103936 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-01 21:25 - Setup PEFT |
|
2024-06-01 21:25 - Setup optimizer |
|
2024-06-01 21:25 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 103936 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-01 21:25 - Setup PEFT |
|
2024-06-01 21:25 - Setup optimizer |
|
2024-06-01 21:25 - Continue training!! |
|
2024-06-01 21:25 - Continue training!! |
|
2024-06-02 08:00 - Cuda check |
|
2024-06-02 08:00 - True |
|
2024-06-02 08:00 - 2 |
|
2024-06-02 08:00 - Configue Model and tokenizer |
|
2024-06-02 08:00 - Cuda check |
|
2024-06-02 08:00 - True |
|
2024-06-02 08:00 - 2 |
|
2024-06-02 08:00 - Configue Model and tokenizer |
|
2024-06-02 08:00 - Memory usage in 0.00 GB |
|
2024-06-02 08:00 - Memory usage in 0.00 GB |
|
2024-06-02 08:00 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_ECDC |
|
test -Jingmei/Pandemic |
|
2024-06-02 08:00 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 7008 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-02 08:00 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 103936 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-02 08:00 - Setup PEFT |
|
2024-06-02 08:00 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_ECDC |
|
test -Jingmei/Pandemic |
|
2024-06-02 08:00 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 7008 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-02 08:00 - Setup optimizer |
|
2024-06-02 08:00 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 103936 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-02 08:00 - Setup PEFT |
|
2024-06-02 08:00 - Setup optimizer |
|
2024-06-02 08:00 - Continue training!! |
|
2024-06-02 08:00 - Continue training!! |
|
2024-06-02 08:28 - Training complete!!! |
|
2024-06-02 08:28 - Training complete!!! |
|
2024-06-02 10:07 - Cuda check |
|
2024-06-02 10:07 - True |
|
2024-06-02 10:07 - 2 |
|
2024-06-02 10:07 - Configue Model and tokenizer |
|
2024-06-02 10:07 - Cuda check |
|
2024-06-02 10:07 - True |
|
2024-06-02 10:07 - 2 |
|
2024-06-02 10:07 - Configue Model and tokenizer |
|
2024-06-02 10:07 - Memory usage in 0.00 GB |
|
2024-06-02 10:07 - Memory usage in 0.00 GB |
|
2024-06-02 10:07 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_CDC |
|
test -Jingmei/Pandemic |
|
2024-06-02 10:07 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_CDC |
|
test -Jingmei/Pandemic |
|
2024-06-02 10:09 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 15208 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-02 10:09 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 15208 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-02 10:14 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 364678 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-02 10:14 - Setup PEFT |
|
2024-06-02 10:14 - Setup optimizer |
|
2024-06-02 10:14 - Continue training!! |
|
2024-06-02 10:14 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 364678 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198964 |
|
}) |
|
}) |
|
2024-06-02 10:14 - Setup PEFT |
|
2024-06-02 10:14 - Setup optimizer |
|
2024-06-02 10:15 - Continue training!! |
|
2024-06-02 20:22 - Training complete!!! |
|
2024-06-02 20:22 - Training complete!!! |
|
2024-06-04 12:41 - Cuda check |
|
2024-06-04 12:41 - True |
|
2024-06-04 12:41 - 3 |
|
2024-06-04 12:41 - Configue Model and tokenizer |
|
2024-06-04 12:41 - Cuda check |
|
2024-06-04 12:41 - True |
|
2024-06-04 12:41 - 3 |
|
2024-06-04 12:41 - Configue Model and tokenizer |
|
2024-06-04 12:41 - Cuda check |
|
2024-06-04 12:41 - True |
|
2024-06-04 12:41 - 3 |
|
2024-06-04 12:41 - Configue Model and tokenizer |
|
2024-06-04 12:42 - Memory usage in 0.00 GB |
|
2024-06-04 12:42 - Memory usage in 0.00 GB |
|
2024-06-04 12:42 - Memory usage in 0.00 GB |
|
2024-06-04 12:42 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic |
|
2024-06-04 12:42 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic |
|
2024-06-04 12:42 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic |
|
2024-06-04 12:44 - Cuda check |
|
2024-06-04 12:44 - True |
|
2024-06-04 12:44 - 3 |
|
2024-06-04 12:44 - Configue Model and tokenizer |
|
2024-06-04 12:44 - Cuda check |
|
2024-06-04 12:44 - True |
|
2024-06-04 12:44 - 3 |
|
2024-06-04 12:44 - Configue Model and tokenizer |
|
2024-06-04 12:44 - Cuda check |
|
2024-06-04 12:44 - True |
|
2024-06-04 12:44 - 3 |
|
2024-06-04 12:44 - Configue Model and tokenizer |
|
2024-06-04 12:44 - Memory usage in 0.00 GB |
|
2024-06-04 12:44 - Memory usage in 0.00 GB |
|
2024-06-04 12:44 - Memory usage in 0.00 GB |
|
2024-06-04 12:44 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic_WHO |
|
2024-06-04 12:44 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic_WHO |
|
2024-06-04 12:44 - Dataset loaded successfully: |
|
train-Jingmei/Pandemic_Books |
|
test -Jingmei/Pandemic_WHO |
|
2024-06-04 12:46 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 5966 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-04 12:46 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 5966 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-04 12:46 - Tokenize data: DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 5966 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 8264 |
|
}) |
|
}) |
|
2024-06-04 12:51 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 388202 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198960 |
|
}) |
|
}) |
|
2024-06-04 12:51 - Setup PEFT |
|
2024-06-04 12:51 - Setup optimizer |
|
2024-06-04 12:51 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 388202 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198960 |
|
}) |
|
}) |
|
2024-06-04 12:51 - Setup PEFT |
|
2024-06-04 12:51 - Split data into chunks:DatasetDict({ |
|
train: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 388202 |
|
}) |
|
test: Dataset({ |
|
features: ['input_ids', 'attention_mask'], |
|
num_rows: 198960 |
|
}) |
|
}) |
|
2024-06-04 12:51 - Setup PEFT |
|
2024-06-04 12:51 - Setup optimizer |
|
2024-06-04 12:51 - Setup optimizer |
|
2024-06-04 12:51 - Continue training!! |
|
2024-06-04 12:51 - Continue training!! |
|
2024-06-04 12:51 - Continue training!! |
|
2024-06-04 12:52 - Training complete!!! |
|
2024-06-04 12:52 - Training complete!!! |
|
|