--- library_name: peft license: apache-2.0 base_model: JackFram/llama-160m tags: - axolotl - generated_from_trainer model-index: - name: ee18d753-a67f-44fb-bd48-52c33d7962f4 results: [] --- [Built with Axolotl](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config axolotl version: `0.4.1` ```yaml adapter: lora base_model: JackFram/llama-160m bf16: true chat_template: llama3 datasets: - data_files: - 0b44824add214a21_train_data.json ds_type: json format: custom path: /workspace/input_data/0b44824add214a21_train_data.json type: field_input: src field_instruction: src_lang field_output: tgt 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: lesso04/ee18d753-a67f-44fb-bd48-52c33d7962f4 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/0b44824add214a21_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: 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: ee18d753-a67f-44fb-bd48-52c33d7962f4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: ee18d753-a67f-44fb-bd48-52c33d7962f4 warmup_steps: 10 weight_decay: 0.01 xformers_attention: false ```

# ee18d753-a67f-44fb-bd48-52c33d7962f4 This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.2689 ## 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 | |:-------------:|:------:|:----:|:---------------:| | 3.488 | 0.0206 | 1 | 3.5999 | | 3.2032 | 0.1856 | 9 | 3.2120 | | 2.995 | 0.3711 | 18 | 2.9115 | | 2.7597 | 0.5567 | 27 | 2.6847 | | 2.5851 | 0.7423 | 36 | 2.5497 | | 2.4121 | 0.9278 | 45 | 2.4569 | | 2.2305 | 1.1134 | 54 | 2.3804 | | 2.3589 | 1.2990 | 63 | 2.3151 | | 2.1673 | 1.4845 | 72 | 2.2855 | | 2.3527 | 1.6701 | 81 | 2.2727 | | 2.2403 | 1.8557 | 90 | 2.2702 | | 2.2284 | 2.0412 | 99 | 2.2689 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1