Upload README.md

README.md

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+---
+license: mit
+library_name: peft
+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