09959fac70
* feat: update mistral common * feat: add mistral3processor * fix: loading * fix: cast pixel_values to fp32 * fix: image tensor conversion * feat: add FA2 support for pixtral based models * fix: update mistral small 3.1 to use native tokenizer * fix: install tips * fix: improve info on sample dataset files * chore: move mistral configs into subfolders * fix: remove unneeded patch * fix: indent * feat: add integration tests * chore: move * feat: add magistral 2509 docs and example * fix: convert tensor to bool * feat: expand tests * chore: move tests
69 lines
1.3 KiB
YAML
69 lines
1.3 KiB
YAML
base_model: mistralai/Mistral-7B-v0.1
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# optionally might have model_type or tokenizer_type
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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datasets:
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- path: mhenrichsen/alpaca_2k_test
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0
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output_dir: ./outputs/lora-out
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eval_sample_packing: false
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adapter: lora
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lora_model_dir:
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sequence_len: 4096
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sample_packing: true
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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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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gradient_accumulation_steps: 8
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micro_batch_size: 1
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num_epochs: 2
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 0.0002
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bf16: auto
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fp16: false
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tf32: true
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gradient_checkpointing: true
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resume_from_checkpoint:
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logging_steps: 1
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flash_attention: false
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sdp_attention: true
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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_ratio: 0.1
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.0
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special_tokens:
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# save_first_step: true # uncomment this to validate checkpoint saving works with your config
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