初始化项目，由ModelHub XC社区提供模型

Model: Polygl0t/Tucano2-qwen-1.5B-Base
Source: Original Platform

training_config.yaml

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+# Directory settings
+checkpoint_dir: "/lustre/scratch/data/polyglot_datasets/portuguese/checkpoints/models/Tucano2-qwen-1.5B-Base"
+train_dataset_dir:
+  # Total: ~100B
+  # Web Text (~70B, 70%)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2/3_10b # 12B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2/4 # 28B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2/4 # 28B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2/5 # 0.1B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2/5 # 0.1B (PT)
+  # Synthetic Text (~30B, 30%)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2_synth # 10B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2_synth # 10B (PT)
+  - /lustre/scratch/data/polyglot_datasets/portuguese/tokenized/gigaverbo_v2_synth # 10B (PT)
+val_dataset_dir: "/lustre/scratch/data/polyglot_datasets/portuguese/tokenized/validation"
+dataset_type: "parquet"
+cache_dir: "/lustre/mlnvme/data/nanotronics/.cache"
+
+# Data loading settings
+pin_memory: true
+num_workers_for_dataloader: 16
+shuffle_dataset: true
+mask_eos_token: false
+mask_pad_token: false
+
+# Model architecture settings
+vocab_size: 49152
+num_hidden_layers: 28
+num_attention_heads: 16
+num_key_value_heads: 8
+head_dim: 128
+hidden_size: 2048
+intermediate_size: 6144
+max_position_embeddings: 4096
+tie_word_embeddings: true
+hidden_act: "silu"
+output_hidden_states: false
+attn_implementation: "flash_attention_2"
+use_cache: false
+no_rope_layer_interval: null
+rope_theta: 1000000.0
+rope_scale_factor: null
+rms_norm_eps: 0.000001
+
+# Training settings
+total_batch_size: 1048576
+micro_batch_size: 4
+eval_micro_batch_size: 4
+num_train_epochs: 1
+warmup_steps: 200
+max_learning_rate: 0.0001
+min_learning_rate: 0.0
+muon_learning_rate: 0.001
+weight_decay: 0.1
+beta1: 0.9
+beta2: 0.95
+eps: 0.00000001
+lr_decay_type: "cosine"
+use_sqrt: true
+lr_decay_iters_coef: 1.
+seed: 42
+max_steps: 100000
+max_grad_norm: 1.0
+
+# Precision and optimization settings
+torch_compile: false
+mat_mul_precision: "highest"
+tf32: true
+bf16: true
+gradient_checkpointing: false
+use_liger_kernel: true
+static_graph: false
+
+# Hub settings
+push_to_hub: false
+hub_token: null
+hub_model_id: null
+
+# Tokenizer and Reference model
+tokenizer_name_or_path: "/lustre/scratch/data/polyglot_datasets/portuguese/checkpoints/models/Tucano2-qwen-1.5B"
+chat_template_path: null
+reference_model: "/lustre/scratch/data/polyglot_datasets/portuguese/checkpoints/models/Tucano2-qwen-1.5B"
+continual_pretraining: true
+
+# Checkpoint settings
+resume_from_checkpoint: null
+checkpointing_steps: 2500
+begin_new_stage: false
+stage_name: "single_cosine"
+
+# Miscellaneous settings
+sanity_check: false
+sanity_check_num_samples: 100000
+wandb_token: null
+wandb_id: "tucano2-qwen-1.5b"
+wandb_project: "Polyglot"
+wandb_desc: "Developing LLMs for low-resource languages"