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README.md

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+---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- generated_from_trainer
+datasets:
+- ugaoo/rephased_hf_lmharness
+model-index:
+- name: out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_rephased_hf_lmharness
+  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/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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.8.0.dev0`
+```yaml
+base_model: meta-llama/Llama-3.1-8B-Instruct
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+  - path: ugaoo/rephased_hf_lmharness
+    type: alpaca
+val_set_size: 0
+output_dir: ./out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_rephased_hf_lmharness
+
+sequence_len: 4000
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter: qlora
+lora_r: 256
+lora_alpha: 512
+lora_dropout: 0.05
+lora_target_linear: true
+lora_target_modules:
+  - q_proj
+  - k_proj
+  - v_proj
+  - o_proj
+  - up_proj
+  - down_proj
+  - gate_proj
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+ 
+wandb_project: testsearch
+wandb_entity:
+wandb_watch: 
+wandb_name: meta_llama_Llama_3.1_8B_Instruct_ugaoo_rephased_hf_lmharness
+wandb_log_model:
+
+gradient_accumulation_steps: 3
+micro_batch_size: 4
+num_epochs: 6
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 5e-6
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 100
+evals_per_epoch: 6
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+save_total_limit: 6
+special_tokens:
+   pad_token: <|end_of_text|>
+```
+
+</details><br>
+
+# out/meta_llama_Llama_3.1_8B_Instruct_ugaoo_rephased_hf_lmharness
+
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the ugaoo/rephased_hf_lmharness dataset.
+
+## 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: 5e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 12
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 6.0
+
+### Training results
+
+
+
+### Framework versions
+
+- PEFT 0.14.0
+- Transformers 4.49.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0