| --- |
| license: mit |
| datasets: |
| - OEvortex/vortex-mini |
| tags: |
| - generated_from_trainer |
| base_model: ahxt/LiteLlama-460M-1T |
| model-index: |
| - name: qlora-out |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
| <details><summary>See axolotl config</summary> |
|
|
| axolotl version: `0.4.0` |
| ```yaml |
| adapter: qlora |
| additional_layers: 2 |
| base_model: ahxt/LiteLlama-460M-1T |
| bf16: false |
| dataset_prepared_path: null |
| datasets: |
| - path: OEvortex/vortex-mini |
| type: alpaca |
| debug: null |
| deepspeed: null |
| early_stopping_patience: null |
| embedding_size: 256 |
| evals_per_epoch: null |
| flash_attention: false |
| fp16: true |
| fsdp: null |
| fsdp_config: null |
| gradient_accumulation_steps: 1 |
| gradient_checkpointing: true |
| group_by_length: false |
| hidden_size: 512 |
| is_llama_derived_model: false |
| learning_rate: 0.0002 |
| load_in_4bit: true |
| load_in_8bit: false |
| local_rank: null |
| logging_steps: 1 |
| lora_alpha: 16 |
| lora_dropout: 0.05 |
| lora_fan_in_fan_out: null |
| lora_model_dir: null |
| lora_r: 32 |
| lora_target_linear: true |
| lora_target_modules: null |
| lr_scheduler: cosine |
| max_steps: 20 |
| micro_batch_size: 1 |
| mlflow_experiment_name: colab-example |
| model_type: LlamaForCausalLM |
| num_epochs: 4 |
| optimizer: paged_adamw_32bit |
| output_dir: ./qlora-out |
| pad_to_sequence_len: true |
| resume_from_checkpoint: null |
| sample_packing: true |
| saves_per_epoch: null |
| sequence_len: 1096 |
| special_tokens: null |
| strict: false |
| tf32: false |
| tokenizer_type: GPT2Tokenizer |
| train_on_inputs: false |
| val_set_size: 0.05 |
| wandb_entity: null |
| wandb_log_model: null |
| wandb_name: null |
| wandb_project: null |
| wandb_watch: null |
| warmup_steps: 10 |
| weight_decay: 0.0 |
| xformers_attention: null |
| |
| ``` |
|
|
| </details><br> |
|
|
| # qlora-out |
|
|
| This model is a fine-tuned version of [ahxt/LiteLlama-460M-1T](https://huggingface.co/ahxt/LiteLlama-460M-1T) 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: 0.0002 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - training_steps: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 2.4442 | 0.0 | 20 | nan | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.8.2 |
| - Transformers 4.38.0.dev0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
