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--- |
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license: apache-2.0 |
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datasets: |
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- Crystalcareai/openhermes_200k_unfiltered |
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language: |
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- en |
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library_name: transformers |
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base_model: h2oai/h2o-danube2-1.8b-base |
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tags: |
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- llama-factory |
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- unsloth |
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--- |
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# h2o-danube2 with ChatML template |
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This is a [BAdam](https://arxiv.org/abs/2404.02827 "BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models") and [LoRA+](https://arxiv.org/abs/2402.12354 "LoRA+: Efficient Low Rank Adaptation of Large Models") fine-tuned danube2 base model. It uses the ChatML template and was trained on the [openhermes-unfiltered](https://huggingface.co/datasets/Crystalcareai/openhermes_200k_unfiltered). |
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## Quants |
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Thank you [mradermacher](https://huggingface.co/mradermacher)! |
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- [mradermacher/danube2-1.8b-openhermes-GGUF](https://huggingface.co/mradermacher/danube2-1.8b-openhermes-GGUF) |
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## Template |
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```jinja |
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<|im_start|>user |
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{{instruction}}<|im_end|> |
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<|im_start|>assistant |
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{{response}}<|im_end|> |
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``` |
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## BAdam |
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**System:** You are a helpful assistant. |
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```yaml |
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### model |
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model_name_or_path: danube2-base-chatml |
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### method |
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stage: sft |
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do_train: true |
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finetuning_type: full |
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use_badam: true |
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badam_switch_mode: ascending |
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badam_switch_interval: 50 |
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badam_verbose: 1 |
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badam_start_block: 10 |
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seed: 720 |
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### dataset |
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dataset: openhermes_unfiltered |
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template: ninja_chatml |
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cutoff_len: 8192 |
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overwrite_cache: false |
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preprocessing_num_workers: 12 |
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### output |
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output_dir: openhermes-chatml-badam |
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logging_steps: 5 |
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save_steps: 1 |
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save_strategy: epoch |
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plot_loss: true |
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overwrite_output_dir: false |
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### train |
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per_device_train_batch_size: 2 |
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gradient_accumulation_steps: 8 |
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learning_rate: 0.00001 |
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num_train_epochs: 1 |
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lr_scheduler_type: constant_with_warmup |
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warmup_ratio: 0.01 |
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bf16: true |
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flash_attn: fa2 |
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### eval |
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val_size: 0.01 |
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per_device_eval_batch_size: 1 |
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eval_strategy: steps |
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eval_steps: 2000 |
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``` |
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### BAdam Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.7971 | 0.1748 | 2000 | 0.7418 | |
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| 0.6815 | 0.3496 | 4000 | 0.7178 | |
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| 0.6593 | 0.5245 | 6000 | 0.7055 | |
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| 0.6923 | 0.6993 | 8000 | 0.6960 | |
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| 0.6942 | 0.8741 | 10000 | 0.6877 | |
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## QLoRA+ |
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```yaml |
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### model |
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model_name_or_path: openhermes-chatml-badam |
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### method |
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stage: sft |
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do_train: true |
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finetuning_type: lora |
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lora_target: all |
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loraplus_lr_ratio: 16.0 |
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lora_rank: 8 |
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lora_alpha: 16 |
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use_unsloth: true |
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quantization_bit: 4 |
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upcast_layernorm: true |
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seed: 3141 |
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### dataset |
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dataset: openhermes_unfiltered |
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template: hermes_chatml |
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cutoff_len: 8192 |
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overwrite_cache: false |
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preprocessing_num_workers: 12 |
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### output |
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output_dir: openhermes-chatml-badam/loraplus |
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logging_steps: 1 |
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save_steps: 1 |
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save_strategy: epoch |
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plot_loss: true |
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overwrite_output_dir: false |
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### train |
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per_device_train_batch_size: 4 |
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gradient_accumulation_steps: 4 |
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learning_rate: 0.0001 |
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num_train_epochs: 1.0 |
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lr_scheduler_type: cosine |
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warmup_ratio: 0.01 |
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bf16: true |
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flash_attn: fa2 |
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#neftune_noise_alpha: 5 |
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### eval |
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val_size: 0.02 |
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per_device_eval_batch_size: 1 |
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eval_strategy: steps |
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eval_steps: 1000 |
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``` |
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### QLoRA+ Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.6523 | 0.0883 | 1000 | 0.7126 | |
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| 0.6398 | 0.1766 | 2000 | 0.7086 | |
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| 0.6865 | 0.2649 | 3000 | 0.7001 | |
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| 0.6714 | 0.3532 | 4000 | 0.6917 | |
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| 0.7213 | 0.4415 | 5000 | 0.6819 | |
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| 0.7764 | 0.5298 | 6000 | 0.6721 | |
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| 0.6931 | 0.6181 | 7000 | 0.6638 | |
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| 0.6632 | 0.7064 | 8000 | 0.6560 | |
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| 0.5966 | 0.7947 | 9000 | 0.6514 | |
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| 0.6339 | 0.8830 | 10000 | 0.6482 | |
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| 0.4987 | 0.9713 | 11000 | 0.6472 | |
