![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/VTacthtA6N97SqD23WtwB.png) # 🔬 Einstein-v4-Qwen-1.5-32B This model is a [QLoRA](https://arxiv.org/abs/2305.14314) fine-tuned version of [Qwen/Qwen1.5-32B](https://huggingface.co/Qwen/Qwen1.5-32B) on diverse datasets. This model is finetuned using `8xRTX3090` + `1xRTXA6000` using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl). This model's training was sponsored by [sablo.ai](https://sablo.ai).

See axolotl config

axolotl version: `0.4.0` ```yaml base_model: Qwen/Qwen1.5-32B model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: true strict: false chat_template: chatml datasets: - path: data/merged_all.json ds_type: json type: alpaca conversation: chatml - path: data/capybara_sharegpt.json ds_type: json type: sharegpt conversation: chatml - path: data/synthia-v1.3_sharegpt_12500.json ds_type: json type: sharegpt conversation: chatml - path: data/cot_alpaca_gpt4_extracted_openhermes_2.5_sharegpt.json ds_type: json type: sharegpt conversation: chatml - path: data/slimorca_dedup_filtered_95k_sharegpt.json ds_type: json type: sharegpt conversation: chatml - path: data/airoboros_3.2_without_contextual_slimorca_orca_sharegpt.json ds_type: json type: sharegpt conversation: chatml dataset_prepared_path: last_run_prepared val_set_size: 0 # because we won't eval, out of memory :( output_dir: ./Einstein-v4-Qwen-1.5-32B-model sequence_len: 4096 sample_packing: true pad_to_sequence_len: true eval_sample_packing: false adapter: qlora lora_model_dir: lora_r: 64 lora_alpha: 32 lora_dropout: 0.05 lora_target_linear: true lora_fan_in_fan_out: lora_modules_to_save: - "embed_tokens" - "lm_head" wandb_project: Einstein wandb_entity: wandb_watch: wandb_name: Einstein-v4-Qwen-1.5-32B-qlora-2-epoch wandb_log_model: hub_model_id: Weyaxi/Einstein-v4-Qwen-1.5-32B save_safetensors: true gradient_accumulation_steps: 4 micro_batch_size: 1 num_epochs: 2 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 10 evals_per_epoch: 0 # because we won't eval, out of memory :( eval_table_size: eval_table_max_new_tokens: 128 saves_per_epoch: 2 debug: deepspeed: zero3_bf16_cpuoffload_params.json weight_decay: 0.0 fsdp: fsdp_config: special_tokens: bos_token: "~~" eos_token: "<|im_end|>" unk_token: "" tokens: - "<|im_start|>" ```~~

# 💬 Prompt Template You can use this prompt template while using the model: ### ChatML ``` <|im_start|>system {system}<|im_end|> <|im_start|>user {user}<|im_end|> <|im_start|>assistant {asistant}<|im_end|> ``` This prompt template is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating), which means you can format messages using the `tokenizer.apply_chat_template()` method: ```python messages = [ {"role": "system", "content": "You are helpful AI asistant."}, {"role": "user", "content": "Hello!"} ] gen_input = tokenizer.apply_chat_template(message, return_tensors="pt") model.generate(**gen_input) ``` # 🔄 Quantizationed versions Quantizationed versions of this model is currently not available. # 🎯 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Weyaxi__Einstein-v4-Qwen-1.5-32B) | Metric |Value| |---------------------------------|----:| |Avg. |68.54| |AI2 Reasoning Challenge (25-Shot)|62.37| |HellaSwag (10-Shot) |83.85| |MMLU (5-Shot) |74.04| |TruthfulQA (0-shot) |58.86| |Winogrande (5-shot) |80.43| |GSM8k (5-shot) |51.71| # 🤖 Additional information about training This model is full fine-tuned for 2 epochs. Total number of steps was 3352.
Loss graph
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/0Vp8iDmXi4-XbQCiwQtNP.png)

# 🤝 Acknowledgments Thanks to [sablo.ai](https://sablo.ai) for sponsoring this model. Thanks to all the dataset authors mentioned in the datasets section. Thanks to [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) for making the repository I used to make this model. Thanks to all open source AI community. [](https://github.com/OpenAccess-AI-Collective/axolotl) If you would like to support me: [☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)