Upload README.md with huggingface_hub

README.md

@@ -1,3 +1,151 @@
 ---
-license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: JY623/KoSOLAR-v2.0
+model-index:
+- name: qlora-out/v1.2
+  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
+base_model: JY623/KoSOLAR-v2.0
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+push_dataset_to_hub:
+datasets:
+  - path: kyujinpy/KOR-OpenOrca-Platypus-v3
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./qlora-out/v1.2
+
+adapter: qlora
+lora_model_dir:
+
+sequence_len: 4096
+sample_packing: true
+pad_to_sequence_len: true
+
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 1
+num_epochs: 2
+optimizer: paged_adamw_32bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: false
+
+warmup_steps: 20
+evals_per_epoch: 4
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+```
+
+</details><br>
+
+# qlora-out/v1.2
+
+This model is a fine-tuned version of [JY623/KoSOLAR-v2.0](https://huggingface.co/JY623/KoSOLAR-v2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.1419
+
+## 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
+- distributed_type: multi-GPU
+- num_devices: 7
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 28
+- total_eval_batch_size: 7
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 13.4775       | 0.0   | 1    | 13.4330         |
+| 6.9219        | 0.25  | 64   | 6.2022          |
+| 5.5416        | 0.5   | 128  | 5.2780          |
+| 5.4282        | 0.75  | 192  | 5.1929          |
+| 5.4864        | 1.0   | 256  | 5.1416          |
+| 5.2877        | 1.24  | 320  | 5.1441          |
+| 5.1731        | 1.49  | 384  | 5.1413          |
+| 5.6221        | 1.74  | 448  | 5.1406          |
+| 5.3737        | 1.99  | 512  | 5.1419          |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.40.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.0