Model: Grogros/dm-llama3.2-1BI-LucieFr-Al4-OWT-TV-ablation-h2d4 Source: Original Platform
52 lines
1.1 KiB
YAML
52 lines
1.1 KiB
YAML
alpha: 0.1
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base_model: meta-llama/Llama-3.2-1B-Instruct
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custom_name: TV
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dtype: bfloat16
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lambdas:
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- 1.0
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- 1.0
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- 1.0
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lora_config: null
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loss_types:
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- anti-watermark-tv
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- anti-watermark-tv
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meta_learning_config: null
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n_wm_tokens: 0
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proportions:
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- 0.6
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- 0.2
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- 0.2
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random_training_config: null
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regularization_datasets:
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- !!python/object/apply:finetuning.dataset.DatasetType
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- AlpacaGPT4
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- !!python/object/apply:finetuning.dataset.DatasetType
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- OpenWebText
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sequence_length: 512
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streaming: true
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training_args:
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bf16: false
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do_train: true
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fp16: false
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gradient_accumulation_steps: 16
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gradient_checkpointing: false
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hub_strategy: all_checkpoints
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learning_rate: 2.0e-05
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logging_steps: 10
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lr_scheduler_type: cosine
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max_steps: 2500
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num_train_epochs: 1
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optim: adafactor
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output_dir: Grogros/dm-llama3.2-1BI-LucieFr-Al4-OWT-TV-ablation-h2d4
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overwrite_output_dir: true
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per_device_train_batch_size: 4
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push_to_hub: true
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report_to: none
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save_steps: 500
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save_strategy: steps
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warmup_ratio: 0.1
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watermark_datasets:
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- !!python/object/apply:finetuning.dataset.DatasetType
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- LucieFr
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watermark_eval_config: []
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