Create config_stage_1.yaml
Browse files- config_stage_1.yaml +102 -0
config_stage_1.yaml
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# Directory settings
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checkpoint_dir: "/lustre/scratch/data/polyglot_datasets/bengali/checkpoints/models/LilTii/v2"
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train_dataset_dir:
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# Total: ~99B
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# Bengali Text (~40B)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_1" # 5.8B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_2" # 8.6B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_3" # 4.2B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_4" # 1.5B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_5" # 5.5M (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_1" # 5.8B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_2" # 8.6B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_3" # 4.2B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_4" # 1.5B (ben)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/edu_score_5" # 5.5M (ben)
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# Edu English Text (~35B)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/fineweb_edu/edu_score_3" # 35.B (eng)
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# Reasoning (~14.6B)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/math_meta_reasoning_filtered" # 1.2B (eng)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/math_meta_reasoning_filtered" # 1.2B (eng)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/nvidia_openscience" # 9.8B (eng)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/big_reasoning_traces" # 2.4B (eng)
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# Edu Math Text (~9.5B)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/finemath_34b/edu_score_4" # 8.5B (eng)
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- "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/finemath_34b/edu_score_5" # 1.0B (eng)
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val_dataset_dir: "/lustre/scratch/data/polyglot_datasets/bengali/tokenized/validation_split"
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dataset_type: "parquet"
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cache_dir: "/lustre/mlnvme/data/polyglot/.cache"
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# Data loading settings
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pin_memory: true
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num_workers_for_dataloader: 32
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shuffle_dataset: true
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# Model architecture settings
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vocab_size: 49152
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num_hidden_layers: 28
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num_attention_heads: 16
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num_key_value_heads: 8
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head_dim: null
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hidden_size: 1536
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intermediate_size: 3072
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max_position_embeddings: 4096
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tie_word_embeddings: true
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hidden_act: "silu"
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output_hidden_states: false
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attn_implementation: "flash_attention_2"
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use_cache: false
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no_rope_layer_interval: null
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rope_theta: 50000.0
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rope_scale_factor: null
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rms_norm_eps: 0.000001
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# Training settings
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total_batch_size: 2097152
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micro_batch_size: 16
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eval_micro_batch_size: 8
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num_train_epochs: 1
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warmup_steps: 2000
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max_learning_rate: 0.0007
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min_learning_rate: 0.0
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weight_decay: 0.1
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beta1: 0.9
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beta2: 0.95
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eps: 0.00000001
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lr_decay_type: "wsd"
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lr_decay_iters_coef: 0.0
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seed: 1337
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max_steps: 47500
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max_grad_norm: 1.0
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# Precision and optimization settings
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torch_compile: false
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mat_mul_precision: "highest"
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tf32: true
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bf16: true
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gradient_checkpointing: false
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use_liger_kernel: true
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static_graph: false
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# Hub settings
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push_to_hub: false
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hub_token: null
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hub_model_id: null
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# Tokenizer and Reference model
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tokenizer_name_or_path: "Polygl0t/LilTii-v0.2"
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reference_model: "HuggingFaceTB/SmolLM2-360M"
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# Checkpoint settings
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resume_from_checkpoint: null
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checkpointing_steps: 2500
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begin_new_stage: false
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stage_name: "Warmup-Stable"
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# Miscellaneous settings
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sanity_check: false
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sanity_check_num_samples: 100000
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wandb_token: null
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wandb_id: "LilTii-v0.2"
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wandb_project: "Polyglot"
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wandb_desc: "Developing LLMs for low-resource languages"
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