--- license: mit base_model: microsoft/phi-2 tags: - axolotl - generated_from_trainer model-index: - name: Einstein-v6.1-phi2 results: [] --- [Built with Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config axolotl version: `0.4.0` ```yaml base_model: microsoft/phi-2 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false chat_template: chatml datasets: - path: data/merged_all.json ds_type: json type: alpaca conversation: chatml - path: data/gpteacher-instruct-special-alpaca.json ds_type: json type: gpteacher conversation: chatml - path: data/wizardlm_evol_instruct_70k_random_half.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 - path: data/allenai_wild_chat_gpt4_english_toxic_random_half_4k_sharegpt.json ds_type: json type: sharegpt strict: false conversation: chatml - path: data/pippa_bagel_repo_3k_sharegpt.json ds_type: json type: sharegpt conversation: chatml - path: data/gpt4_data_lmys_1m_sharegpt.json ds_type: json type: sharegpt conversation: chatml - path: data/sharegpt_gpt4_english.json ds_type: json type: sharegpt conversation: chatml - path: data/no_robots_sharegpt.json ds_type: json type: sharegpt strict: false conversation: chatml - path: data/oasst_top1_from_fusechatmixture_sharegpt.json ds_type: json type: sharegpt strict: false conversation: chatml - path: data/everythinglm-data-v3_sharegpt.json ds_type: json type: sharegpt strict: false conversation: chatml dataset_prepared_path: last_run_prepared val_set_size: 0.002 output_dir: ./Einstein-v6.1-phi2-model sequence_len: 2048 sample_packing: true pad_to_sequence_len: true eval_sample_packing: false wandb_project: Einstein wandb_entity: wandb_watch: wandb_name: Einstein-v6.1-phi2-2-epoch wandb_log_model: hub_model_id: Weyaxi/Einstein-v6.1-phi2 save_safetensors: true gradient_accumulation_steps: 4 micro_batch_size: 4 num_epochs: 2 optimizer: adamw_torch # adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.000005 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: 2 # changed eval_table_size: eval_table_max_new_tokens: 128 saves_per_epoch: 1 debug: deepspeed: zero3_bf16.json weight_decay: 0.0 fsdp: fsdp_config: special_tokens: eos_token: "<|im_end|>" pad_token: "<|endoftext|>" tokens: - "<|im_start|>" ```

# Einstein-v6.1-phi2 This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7715 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 9 - gradient_accumulation_steps: 4 - total_train_batch_size: 144 - total_eval_batch_size: 36 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.1058 | 0.0 | 1 | 1.1560 | | 0.8559 | 0.5 | 495 | 0.8058 | | 0.8126 | 1.0 | 990 | 0.7826 | | 0.9133 | 1.48 | 1485 | 0.7715 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2+cu118 - Datasets 2.18.0 - Tokenizers 0.15.0