Streaming SFT support (#3101)
* working * fixes * deprecate --iterable; cleanup * pretrain_multipack_buffer_size -> streaming_multipack_buffer_size * improvements * tests * remove unused * docs, examples * nit * nit * add val_set_size validation * val * nit * min * coderabbito * cleanup * nit * add depr warning, cleanup * nit * fix test, fix quarto * fix * review comments * review comments * fix
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examples/streaming/sft.yaml
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examples/streaming/sft.yaml
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base_model: HuggingFaceTB/SmolLM2-135M
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# Dataset configuration
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datasets:
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- path: tatsu-lab/alpaca
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type: alpaca
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split: train
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# Streaming-specific settings
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streaming: true
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streaming_multipack_buffer_size: 10000
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shuffle_merged_datasets: true
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# Training configuration
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max_steps: 1000
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output_dir: ./outputs/smollm2-135m-sft-streaming
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# Sequence and packing settings
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sequence_len: 1024
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sample_packing: true
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flash_attention: true
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# Batch size settings
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gradient_accumulation_steps: 4
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micro_batch_size: 1
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# Optimizer and scheduler
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 2e-4
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warmup_ratio: 0.1
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weight_decay: 0.0
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# Precision and performance
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bf16: auto
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tf32: true
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# Logging and checkpointing
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logging_steps: 10
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save_strategy: steps
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save_steps: 100
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save_total_limit: 3
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# Weights & Biases (optional)
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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# Special tokens
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special_tokens:
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pad_token: "<|endoftext|>"
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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