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--- |
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base_model: google/gemma-2-9b |
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library_name: peft |
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license: gemma |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: lora-out |
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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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base_model: google/gemma-2-9b |
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sequence_len: 1024 |
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# base model weight quantization |
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load_in_8bit: true |
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# load_in_4bit: true |
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# attention implementation |
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flash_attention: true |
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# finetuned adapter config |
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adapter: lora |
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lora_model_dir: |
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lora_r: 16 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral |
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- embed_tokens |
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- lm_head |
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# if training fails, uncomment above |
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# for details, see https://github.com/huggingface/peft/issues/334#issuecomment-1561727994 |
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### |
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# Dataset Configuration: sqlqa |
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### |
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# datasets: |
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# - path: data.jsonl |
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# type: alpaca |
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datasets: |
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- path: public_train_data.jsonl |
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ds_type: json |
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type: |
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field_instruction: instruction |
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field_input: input |
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field_output: output |
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format: |- |
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[INST] {instruction} |
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{input} [/INST] |
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chat_template: gemma |
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tokens: |
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- "[INST]" |
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- " [/INST]" |
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- "[QL]" |
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- " [/QL]" |
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- "[EXPLANATION]" |
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- " [/EXPLANATION]" |
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# dataset formatting config |
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special_tokens: |
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pad_token: <|end_of_text|> |
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val_set_size: 0.05 |
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### |
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# Training Configuration |
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### |
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# masks the input messages so that the model learns and understands the language w/o being reliant on the input |
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train_on_inputs: false |
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# random seed for better reproducibility |
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seed: 117 |
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# optimizer config |
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optimizer: adamw_bnb_8bit |
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learning_rate: 0.0001 |
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lr_scheduler: cosine |
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num_epochs: 4 |
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micro_batch_size: 4 |
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gradient_accumulation_steps: 1 |
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warmup_steps: 10 |
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# axolotl saving config |
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dataset_prepared_path: last_run_prepared |
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output_dir: ./lora-out |
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# logging and eval config |
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logging_steps: 1 |
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eval_steps: 0.05 |
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# training performance optimization config |
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bf16: auto |
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tf32: false |
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gradient_checkpointing: true |
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### |
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# Miscellaneous Configuration |
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### |
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# when true, prevents over-writing the config from the CLI |
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strict: false |
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# "Don't mess with this, it's here for accelerate and torchrun" -- axolotl docs |
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local_rank: |
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# WANDB |
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wandb_mode: |
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wandb_project: |
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wandb_watch: |
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wandb_name: |
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wandb_run_id: |
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# Multi-GPU |
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# deepspeed: /root/axolotl/deepspeed_configs/zero3_bf16.json |
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# deepspeed: zero3_bf16.json |
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# deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json |
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deepspeed: |
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fsdp: |
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fsdp_config: |
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``` |
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</details><br> |
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# lora-out |
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This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0077 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 117 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.7925 | 0.0385 | 1 | 2.0412 | |
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| 1.6872 | 0.2308 | 6 | 1.6089 | |
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| 0.6967 | 0.4615 | 12 | 0.6328 | |
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| 0.3327 | 0.6923 | 18 | 0.2711 | |
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| 0.1784 | 0.9231 | 24 | 0.1733 | |
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| 0.1136 | 1.1538 | 30 | 0.1190 | |
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| 0.0891 | 1.3846 | 36 | 0.0850 | |
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| 0.0746 | 1.6154 | 42 | 0.0626 | |
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| 0.0522 | 1.8462 | 48 | 0.0465 | |
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| 0.033 | 2.0769 | 54 | 0.0282 | |
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| 0.0333 | 2.3077 | 60 | 0.0225 | |
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| 0.0171 | 2.5385 | 66 | 0.0203 | |
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| 0.0172 | 2.7692 | 72 | 0.0144 | |
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| 0.0095 | 3.0 | 78 | 0.0119 | |
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| 0.0088 | 3.2308 | 84 | 0.0099 | |
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| 0.0054 | 3.4615 | 90 | 0.0089 | |
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| 0.0073 | 3.6923 | 96 | 0.0085 | |
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| 0.0059 | 3.9231 | 102 | 0.0077 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.45.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.0 |
