--- library_name: peft license: apache-2.0 base_model: openlm-research/open_llama_3b tags: - axolotl - generated_from_trainer model-index: - name: cbe324eb-13ec-4f47-aac8-65bea34b4233 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: openlm-research/open_llama_3b bf16: true chat_template: llama3 datasets: - data_files: - 632396fb00eaf0b4_train_data.json ds_type: json format: custom path: /workspace/input_data/632396fb00eaf0b4_train_data.json type: field_input: style field_instruction: caption field_output: desciption format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 2 gradient_checkpointing: true group_by_length: false hub_model_id: lesso11/cbe324eb-13ec-4f47-aac8-65bea34b4233 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 77GiB max_steps: 100 micro_batch_size: 8 mlflow_experiment_name: /tmp/632396fb00eaf0b4_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 25 save_strategy: steps sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cbe324eb-13ec-4f47-aac8-65bea34b4233 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cbe324eb-13ec-4f47-aac8-65bea34b4233 warmup_steps: 10 weight_decay: 0.01 xformers_attention: false ``` </details><br> # cbe324eb-13ec-4f47-aac8-65bea34b4233 This model is a fine-tuned version of [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7116 ## 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: 0.0001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.5907 | 0.0000 | 1 | 2.5595 | | 2.4828 | 0.0002 | 9 | 2.3927 | | 2.106 | 0.0005 | 18 | 1.9979 | | 1.8731 | 0.0007 | 27 | 1.8847 | | 1.7808 | 0.0009 | 36 | 1.8191 | | 1.7983 | 0.0011 | 45 | 1.7852 | | 1.7838 | 0.0014 | 54 | 1.7534 | | 1.7166 | 0.0016 | 63 | 1.7366 | | 1.7272 | 0.0018 | 72 | 1.7245 | | 1.8232 | 0.0021 | 81 | 1.7159 | | 1.6219 | 0.0023 | 90 | 1.7123 | | 1.7225 | 0.0025 | 99 | 1.7116 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1