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83 lines
1.6 KiB
YAML
83 lines
1.6 KiB
YAML
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# Template config, need to change dump_dir, data.root_dir and tokenizer.path
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# Evals can be activated by uncommenting its config
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# python -m launchers.stool config=apps/main/configs/debug.yaml nodes=8 account=fair_amaia_cw_codegen qos=lowest
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dump_dir: /tmp/
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name: "debug"
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steps: 100_000
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probe_freq: null
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seed: 777
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optim:
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lr: 4e-04
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warmup: 500
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lr_min_ratio: 0.1
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clip: 10.0
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distributed:
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fsdp_type: full_shard
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model_dtype: bf16
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matmul_allow_tf32: false
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selective_activation_checkpointing: false
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tp_size: 1
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train_entropy_model: true
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model: null
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entropy_model:
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dim: 768
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n_layers: 14
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n_heads: 12
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max_seqlen: 8192
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# vocab_size: -1
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vocab_size: 260
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ffn_dim_multiplier: 1.0
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sliding_window: 512
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attn_bias_type: "local_block_causal"
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attn_impl: "xformers"
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data:
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s3_profile: blt
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root_dir: ???
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sources:
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dclm_baseline_1.0: 1.0
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batch_size: 2
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prefetch_size: 64
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# seqlen is in terms of patches and
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# max_encoder_seq_length is in terms of bytes.
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# For entropy model, these are the same since 1 patch=1 byte
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seq_len: 8192
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max_encoder_seq_length: 8192
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load_async: true
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preprocess_dir: ???
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# We don't need patches for this model
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add_patches: false
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patcher_args:
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# This doesn't matter since byte entropy model doesn't use patching,
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# so pick the most efficient, so static
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patching_mode: byte
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tokenizer_args:
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name: bytes
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profiling:
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run: false
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checkpoint:
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dump:
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every: 500
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keep: 3
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eval:
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every: 1000
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keep: -1
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logging:
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freq: 10
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eval_on_gpus: 8
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eval:
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dataset_dir: ???
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tasks: ???
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generator:
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max_tokens: 65536
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dtype: bf16
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mp_size: 1
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