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--- |
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license: cc0-1.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Open-Orca/SlimOrca |
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base_model: 152334H/miqu-1-70b-sf |
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model-index: |
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- name: Senku-70B-Full |
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results: [] |
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--- |
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<br/><br/> |
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3.2bpw/h6 exl2 quantization of [ShinojiResearch/Senku-70B-Full](https://huggingface.co/ShinojiResearch/Senku-70B-Full) using default exllamav2 calibration dataset. |
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--- |
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**ORIGINAL CARD:** |
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# ShinojiResearch/Senku-70B-Full |
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[<img src="https://cdna.artstation.com/p/assets/images/images/034/109/324/large/bella-factor-senku-ishigami.jpg?1611427638" width="420">](Senku-70B-Full) |
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## UPDATE: **85.09** EQ-Bench with ChatML teamplate |
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* EQ-Bench: (Mistral) *84.89* -> **85.09** (ChatML) |
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* GSM8k: (Mistral) *77.18* -> **71.04** (ChatML) |
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* Hellaswag: (Mistral) 87.67 -> ?? |
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Finetune of miqu-70b-sf dequant of miqudev's leak of Mistral-70B (allegedly an early mistral medium). My diffs are available under CC-0 (That is the Senku-70B repo, full includes the merge), this is a merge with the leaked model, you can use the other repository to save bandwidth. |
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**Update**: Upon further testing a score of **85.09** was achieved using ChatML instead of Mistral's prompt. |
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## Prompt Template |
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I recommend using the ChatML format instead, I will run more benchmarks. This also fixes the bug with Miqu dequant failing to provide a stop. |
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``` |
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<|im_start|>system |
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Provide some context and/or instructions to the model. |
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<|im_end|> |
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<|im_start|>user |
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The user’s message goes here |
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<|im_end|> |
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<|im_start|>assistant <|im_end|> |
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``` |
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## Kudos |
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`Credit to https://twitter.com/hu_yifei for providing GSM & Hellaswag. It is the first open weight model to dethrone GPT-4 on EQ bench.` |
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## Base Model Details |
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This model is a fine-tuned version of [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) on the Slimorca dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3110 |
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## Training procedure |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: 152334H/miqu-1-70b-sf |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: Open-Orca/SlimOrca |
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type: sharegpt |
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conversation: chatml |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.1 |
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output_dir: ./qlora-out |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: 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_fan_in_fan_out: |
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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: 4 |
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micro_batch_size: 2 |
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num_epochs: 1 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9043 | 0.0 | 1 | 0.6387 | |
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| 0.5612 | 0.25 | 881 | 0.3279 | |
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| 0.6044 | 0.5 | 1762 | 0.3177 | |
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| 0.6592 | 0.75 | 2643 | 0.3110 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ShinojiResearch__Senku-70B-Full) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |75.44| |
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|AI2 Reasoning Challenge (25-Shot)|71.50| |
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|HellaSwag (10-Shot) |87.88| |
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|MMLU (5-Shot) |75.20| |
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|TruthfulQA (0-shot) |61.96| |
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|Winogrande (5-shot) |84.77| |
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|GSM8k (5-shot) |71.34| |
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