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README.md

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+---
+base_model: google/gemma-2-9b
+library_name: peft
+license: gemma
+tags:
+- generated_from_trainer
+model-index:
+- name: lora-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/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: `0.4.1`
+```yaml
+base_model: google/gemma-2-9b
+
+sequence_len: 1024
+
+# base model weight quantization
+load_in_8bit: true
+# load_in_4bit: true
+
+# attention implementation
+flash_attention: true
+
+# finetuned adapter config
+adapter: lora
+lora_model_dir:
+lora_r: 16
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
+  - embed_tokens
+  - lm_head
+
+# if training fails, uncomment above
+# for details, see https://github.com/huggingface/peft/issues/334#issuecomment-1561727994
+
+###
+# Dataset Configuration: sqlqa
+###
+# datasets:
+#   - path: data.jsonl
+#     type: alpaca
+
+datasets:
+  - path: public_train_data.jsonl
+    ds_type: json
+    type:
+      field_instruction: instruction
+      field_input: input
+      field_output: output
+      format: |-
+        [INST] {instruction}
+        {input} [/INST]
+
+chat_template: gemma
+tokens:
+  - "[INST]"
+  - " [/INST]"
+  - "[QL]"
+  - " [/QL]"
+  - "[EXPLANATION]"
+  - " [/EXPLANATION]"
+# dataset formatting config
+
+special_tokens:
+  pad_token: <|end_of_text|>
+
+val_set_size: 0.05
+
+###
+# Training Configuration
+###
+
+# masks the input messages so that the model learns and understands the language w/o being reliant on the input
+train_on_inputs: false
+# random seed for better reproducibility
+seed: 117
+
+# optimizer config
+optimizer: adamw_bnb_8bit
+learning_rate: 0.0001
+lr_scheduler: cosine
+num_epochs: 4
+micro_batch_size: 4
+gradient_accumulation_steps: 1
+warmup_steps: 10
+
+# axolotl saving config
+dataset_prepared_path: last_run_prepared
+output_dir: ./lora-out
+
+# logging and eval config
+logging_steps: 1
+eval_steps: 0.05
+
+# training performance optimization config
+bf16: auto
+tf32: false
+gradient_checkpointing: true
+
+###
+# Miscellaneous Configuration
+###
+
+# when true, prevents over-writing the config from the CLI
+strict: false
+
+# "Don't mess with this, it's here for accelerate and torchrun" -- axolotl docs
+local_rank:
+
+# WANDB
+wandb_mode:
+wandb_project:
+wandb_watch:
+wandb_name:
+wandb_run_id:
+
+# Multi-GPU
+# deepspeed: /root/axolotl/deepspeed_configs/zero3_bf16.json
+# deepspeed: zero3_bf16.json
+# deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
+deepspeed:
+fsdp:
+fsdp_config:
+
+```
+
+</details><br>
+
+# lora-out
+
+This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0077
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 117
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.7925        | 0.0385 | 1    | 2.0412          |
+| 1.6872        | 0.2308 | 6    | 1.6089          |
+| 0.6967        | 0.4615 | 12   | 0.6328          |
+| 0.3327        | 0.6923 | 18   | 0.2711          |
+| 0.1784        | 0.9231 | 24   | 0.1733          |
+| 0.1136        | 1.1538 | 30   | 0.1190          |
+| 0.0891        | 1.3846 | 36   | 0.0850          |
+| 0.0746        | 1.6154 | 42   | 0.0626          |
+| 0.0522        | 1.8462 | 48   | 0.0465          |
+| 0.033         | 2.0769 | 54   | 0.0282          |
+| 0.0333        | 2.3077 | 60   | 0.0225          |
+| 0.0171        | 2.5385 | 66   | 0.0203          |
+| 0.0172        | 2.7692 | 72   | 0.0144          |
+| 0.0095        | 3.0    | 78   | 0.0119          |
+| 0.0088        | 3.2308 | 84   | 0.0099          |
+| 0.0054        | 3.4615 | 90   | 0.0089          |
+| 0.0073        | 3.6923 | 96   | 0.0085          |
+| 0.0059        | 3.9231 | 102  | 0.0077          |
+
+
+### Framework versions
+
+- PEFT 0.13.0
+- Transformers 4.45.1
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.0