--- library_name: peft license: llama3 base_model: aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct tags: - axolotl - generated_from_trainer model-index: - name: 8daaa4ae-a55a-41cc-b2bd-80d36516e1dd results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 9c074260b7c494a6_train_data.json ds_type: json format: custom path: /workspace/input_data/9c074260b7c494a6_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: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 5 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 6 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik1987/8daaa4ae-a55a-41cc-b2bd-80d36516e1dd 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: 64 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 32 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 70GiB max_steps: 50 micro_batch_size: 4 mlflow_experiment_name: /tmp/9c074260b7c494a6_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: 4056 strict: false tf32: false tokenizer_type: AutoTokenizer torch_dtype: bfloat16 train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 8daaa4ae-a55a-41cc-b2bd-80d36516e1dd wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 8daaa4ae-a55a-41cc-b2bd-80d36516e1dd warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ```

# 8daaa4ae-a55a-41cc-b2bd-80d36516e1dd This model is a fine-tuned version of [aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct](https://huggingface.co/aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 6 - total_train_batch_size: 24 - 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: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0005 | 1 | nan | | 0.0 | 0.0020 | 4 | nan | | 0.0 | 0.0040 | 8 | nan | | 0.0 | 0.0059 | 12 | nan | | 0.0 | 0.0079 | 16 | nan | | 0.0 | 0.0099 | 20 | nan | | 0.0 | 0.0119 | 24 | nan | | 0.0 | 0.0139 | 28 | nan | | 0.0 | 0.0159 | 32 | nan | | 0.0 | 0.0178 | 36 | nan | | 0.0 | 0.0198 | 40 | nan | | 0.0 | 0.0218 | 44 | nan | | 0.0 | 0.0238 | 48 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1