--- library_name: transformers license: apache-2.0 base_model: alpindale/Mistral-7B-v0.2-hf tags: - generated_from_trainer model-index: - name: army-pretraining results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml base_model: alpindale/Mistral-7B-v0.2-hf tokenizer_type: AutoTokenizer is_mistral_derived_model: true load_in_8bit: false load_in_4bit: false strict: false datasets: - path: json data_files: hidden_pretraining-us-army.jsonl ds_type: json type: completion dataset_prepared_path: last_run_prepared output_dir: ./army-pretraining sequence_len: 4096 sample_packing: false pad_to_sequence_len: true shuffle_merged_datasets: true wandb_project: mistral-army wandb_entity: wandb_watch: wandb_run_id: wandb_log_model: gradient_accumulation_steps: 6 micro_batch_size: 2 eval_batch_size: 1 num_epochs: 11 optimizer: paged_adamw_8bit lr_scheduler: cosine learning_rate: 0.000020 weight_decay: 0 # Gradient clipping max norm max_grad_norm: 1.0 noisy_embedding_alpha: 0 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: false gradient_checkpointing: unsloth early_stopping_patience: resume_from_checkpoint: logging_steps: 1 xformers_attention: flash_attention: true chat_template: chatml warmup_ratio: 0.5 auto_resume_from_checkpoints: false #warmup_ratio: 0.5 eval_steps: 10 saves_per_epoch: 1 eval_sample_packing: false save_total_limit: 3 debug: deepspeed: deepspeed_configs/zero2.json special_tokens: pad_token: "<|end_of_text|>" ```

# army-pretraining This model is a fine-tuned version of [alpindale/Mistral-7B-v0.2-hf](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) 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: 2e-05 - train_batch_size: 2 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 6 - gradient_accumulation_steps: 6 - total_train_batch_size: 72 - total_eval_batch_size: 6 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 136 - num_epochs: 11 ### Training results ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1