Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model: h2oai/h2o-danube2-1.8b-base
+datasets:
+- TIGER-Lab/MathInstruct
+language:
+- en
+library_name: transformers
+tags:
+- llama-factory
+- unsloth
+---
+# h2o-danube2 with ChatML template
+
+This model was first fine-tuned with [BAdam](https://arxiv.org/abs/2404.02827 "BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models") on [TIGER-Lab/MathInstruct](https://huggingface.co/datasets/TIGER-Lab/MathInstruct) using LLama-Factory.
+
+## Template
+
+```jinja
+<|im_start|>system
+You are a helpful assistant specialised in mathematics.<|im_end|>
+<|im_start|>user
+{{instruction}}<|im_end|>
+<|im_start|>assistant
+{{response}}<|im_end|>
+```
+
+## BAdam config
+
+```yaml
+### model
+model_name_or_path: danube2-base-chatml
+
+### method
+stage: sft
+do_train: true
+finetuning_type: full
+use_badam: true
+badam_switch_mode: ascending
+badam_switch_interval: 50
+badam_verbose: 1
+badam_start_block: 7
+seed: 5772
+
+### dataset
+dataset: mathinstruct
+template: ninja_chatml
+cutoff_len: 8192
+overwrite_cache: false
+preprocessing_num_workers: 12
+
+### output
+output_dir: mathinstruct-chatml-badam
+logging_steps: 5
+save_steps: 1
+save_strategy: epoch
+plot_loss: true
+overwrite_output_dir: false
+
+### train
+per_device_train_batch_size: 4
+gradient_accumulation_steps: 4
+learning_rate: 0.000005
+num_train_epochs: 1
+lr_scheduler_type: cosine
+warmup_ratio: 0.01
+pure_bf16: true
+flash_attn: fa2
+
+### eval
+val_size: 0.01
+per_device_eval_batch_size: 1
+eval_strategy: steps
+eval_steps: 1000
+```