--- license: apache-2.0 base_model: mistralai/Mistral-7B-v0.3 tags: - axolotl - generated_from_trainer model-index: - name: Mistral-7B-magpie-v1.0 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml base_model: mistralai/Mistral-7B-v0.3 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false load_in_4bit: false strict: false datasets: - path: Magpie-Align/Magpie-Pro-MT-300K-v0.1 type: sharegpt conversation: llama3 - path: Magpie-Align/Magpie-Reasoning-150K type: sharegpt conversation: llama3 chat_template: llama3 dataset_prepared_path: ./datasets/m7b-magpie output_dir: ./outputs/m7b-magpie-v1.0 sequence_len: 8192 sample_packing: true pad_to_sequence_len: true wandb_project: lm-evals wandb_entity: wandb_watch: wandb_name: Mistral-7B-magpie-v1.0 wandb_log_model: hub_model_id: penfever/Mistral-7B-magpie-v1.0 gradient_accumulation_steps: 8 micro_batch_size: 1 num_epochs: 3 optimizer: paged_adamw_8bit lr_scheduler: cosine learning_rate: 5e-6 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32: false gradient_checkpointing: true gradient_checkpointing_kwargs: use_reentrant: false early_stopping_patience: resume_from_checkpoint: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 100 eval_table_size: saves_per_epoch: 1 debug: deepspeed: weight_decay: 0.0 fsdp: fsdp_config: special_tokens: bos_token: <|begin_of_text|> eos_token: <|end_of_text|> pad_token: <|end_of_text|> tokens: - "<|start_header_id|>" - "<|end_header_id|>" - "<|eot_id|>" ```

[Visualize in Weights & Biases](https://wandb.ai/nyu-dice-lab/lm-evals/runs/6s14gjd3) # Mistral-7B-magpie-v1.0 This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the None dataset. ## 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: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.43.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1