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Saving train state of step 5000
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# Model arguments
model_name_or_path: sanchit-gandhi/Mistral-1.5B-Instruct-v0.2
teacher_model_name_or_path: mistralai/Mistral-7B-Instruct-v0.2
tokenizer_name: mistralai/Mistral-7B-Instruct-v0.2
dtype: bfloat16
load_teacher_in_4bit: true
# Data arguments
train_dataset_name: HuggingFaceTB/cosmopedia
train_dataset_config_name:
- auto_math_text
- khanacademy
- openstax
- stanford
- stories
- web_samples_v1
- web_samples_v2
- wikihow
train_split_name: train[1000:]
eval_split_name: train[:1000]
max_steps: 200000
max_train_samples: 20000000
# Training arguments
do_train: true
do_eval: true
per_device_eval_batch_size: 8
per_device_train_batch_size: 8
learning_rate: 0.0001
warmup_steps: 500
gradient_checkpointing: true
dataloader_num_workers: 4
preprocessing_num_workers: 32
ddp_timeout: 7200
save_strategy: steps
save_steps: 5000
evaluation_strategy: steps
eval_steps: 5000
logging_steps: 25
output_router_logits: true
report_to: all
output_dir: ./
overwrite_output_dir: false
save_total_limit: 1
wandb_project: distil-mistral
push_to_hub: true