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axolotl/examples/streaming/sft.yaml

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YAML

base_model: HuggingFaceTB/SmolLM2-135M
# Dataset configuration
datasets:
- path: tatsu-lab/alpaca
type: alpaca
split: train
# Streaming-specific settings
streaming: true
streaming_multipack_buffer_size: 10000
shuffle_merged_datasets: true
# Training configuration
max_steps: 1000
output_dir: ./outputs/smollm2-135m-sft-streaming
# Sequence and packing settings
sequence_len: 1024
sample_packing: true
attn_implementation: flash_attention_2
# Batch size settings
gradient_accumulation_steps: 4
micro_batch_size: 1
# Optimizer and scheduler
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 2e-4
warmup_ratio: 0.1
weight_decay: 0.0
# Precision and performance
bf16: auto
tf32: true
# Logging and checkpointing
logging_steps: 10
save_strategy: steps
save_steps: 100
save_total_limit: 3
# Weights & Biases (optional)
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
# Special tokens
special_tokens:
pad_token: "<|endoftext|>"
# save_first_step: true # uncomment this to validate checkpoint saving works with your config