--- library_name: peft license: apache-2.0 base_model: tiiuae/falcon-rw-1b tags: - axolotl - generated_from_trainer model-index: - name: 69b7fab1-2f9b-4014-a535-30d75d430a19 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml accelerate_config: dynamo_backend: inductor mixed_precision: bf16 num_machines: 1 num_processes: auto use_cpu: false adapter: lora base_model: tiiuae/falcon-rw-1b bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 071b1ad3c6556dc8_train_data.json ds_type: json format: custom path: /workspace/input_data/071b1ad3c6556dc8_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 16 gradient_checkpointing: true group_by_length: false hub_model_id: VERSIL91/69b7fab1-2f9b-4014-a535-30d75d430a19 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 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 lora_target_modules: - q_proj - v_proj lr_scheduler: cosine max_memory: 0: 70GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/071b1ad3c6556dc8_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true quantization_config: llm_int8_enable_fp32_cpu_offload: true load_in_8bit: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 4056 special_tokens: pad_token: <|endoftext|> strict: false tf32: false tokenizer_type: AutoTokenizer torch_compile: true train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 69b7fab1-2f9b-4014-a535-30d75d430a19 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 69b7fab1-2f9b-4014-a535-30d75d430a19 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ```

# 69b7fab1-2f9b-4014-a535-30d75d430a19 This model is a fine-tuned version of [tiiuae/falcon-rw-1b](https://huggingface.co/tiiuae/falcon-rw-1b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1386 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_BNB 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: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 20.2109 | 0.0003 | 1 | 1.4424 | | 18.7695 | 0.0036 | 13 | 1.2370 | | 19.375 | 0.0073 | 26 | 1.1682 | | 17.5781 | 0.0109 | 39 | 1.1386 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1