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--- |
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library_name: peft |
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license: other |
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base_model: huggyllama/llama-7b |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: fd33a073-1074-445c-9345-a5b1c5007d55 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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adapter: lora |
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base_model: huggyllama/llama-7b |
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bf16: auto |
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chat_template: llama3 |
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cosine_min_lr_ratio: 0.1 |
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data_processes: 4 |
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dataset_prepared_path: null |
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datasets: |
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- data_files: |
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- e4f54eb5c17207cb_train_data.json |
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ds_type: json |
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format: custom |
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num_proc: 4 |
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path: /workspace/input_data/e4f54eb5c17207cb_train_data.json |
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streaming: true |
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type: |
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field_instruction: sentence1 |
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field_output: sentence2 |
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format: '{instruction}' |
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no_input_format: '{instruction}' |
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system_format: '{system}' |
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system_prompt: '' |
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debug: null |
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deepspeed: null |
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device_map: |
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lm_head: 3 |
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model.embed_tokens: 0 |
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model.layers.0: 0 |
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model.layers.1: 0 |
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model.layers.10: 3 |
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model.layers.11: 3 |
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model.layers.2: 0 |
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model.layers.3: 1 |
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model.layers.4: 1 |
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model.layers.5: 1 |
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model.layers.6: 2 |
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model.layers.7: 2 |
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model.layers.8: 2 |
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model.layers.9: 3 |
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model.norm: 3 |
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do_eval: true |
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early_stopping_patience: 1 |
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eval_batch_size: 1 |
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eval_sample_packing: false |
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eval_steps: 25 |
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evaluation_strategy: steps |
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flash_attention: false |
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fp16: null |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 32 |
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gradient_checkpointing: true |
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group_by_length: true |
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hub_model_id: eeeebbb2/fd33a073-1074-445c-9345-a5b1c5007d55 |
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hub_strategy: checkpoint |
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hub_token: null |
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learning_rate: 0.0001 |
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load_in_4bit: false |
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load_in_8bit: false |
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local_rank: null |
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logging_steps: 1 |
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lora_alpha: 64 |
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lora_dropout: 0.05 |
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lora_fan_in_fan_out: null |
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lora_model_dir: null |
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lora_r: 32 |
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lora_target_linear: true |
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lora_target_modules: |
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- q_proj |
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- v_proj |
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lr_scheduler: cosine |
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max_grad_norm: 0.3 |
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max_memory: |
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0: 60GB |
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1: 70GB |
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2: 70GB |
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3: 70GB |
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cpu: 96GB |
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max_steps: 50 |
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micro_batch_size: 1 |
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mixed_precision: bf16 |
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mlflow_experiment_name: /tmp/e4f54eb5c17207cb_train_data.json |
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model_type: AutoModelForCausalLM |
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num_epochs: 3 |
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optim_args: |
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adam_beta1: 0.9 |
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adam_beta2: 0.95 |
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adam_epsilon: 1e-5 |
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optimizer: adamw_torch |
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output_dir: miner_id_24 |
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pad_to_sequence_len: true |
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resume_from_checkpoint: null |
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s2_attention: null |
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sample_packing: false |
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save_steps: 25 |
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save_strategy: steps |
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sequence_len: 2048 |
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special_tokens: |
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pad_token: </s> |
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strict: false |
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tf32: false |
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tokenizer_type: AutoTokenizer |
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torch_compile: false |
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torch_dtype: bfloat16 |
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train_on_inputs: false |
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trust_remote_code: true |
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use_cache: false |
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val_set_size: 50 |
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wandb_entity: null |
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wandb_mode: online |
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wandb_name: fd33a073-1074-445c-9345-a5b1c5007d55 |
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wandb_project: Public_TuningSN |
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wandb_runid: fd33a073-1074-445c-9345-a5b1c5007d55 |
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warmup_ratio: 0.05 |
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weight_decay: 0.01 |
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xformers_attention: null |
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``` |
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</details><br> |
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# fd33a073-1074-445c-9345-a5b1c5007d55 |
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This model is a fine-tuned version of [huggyllama/llama-7b](https://huggingface.co/huggyllama/llama-7b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 4 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 2 |
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- training_steps: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.0 | 0.0060 | 1 | nan | |
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| 0.0 | 0.1500 | 25 | nan | |
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| 0.0 | 0.3000 | 50 | nan | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.0 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
