---
library_name: peft
base_model: oopsung/llama2-7b-koNqa-test-v1
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 3fa85917-ca48-4a86-9402-f6e97a492e27
  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
adapter: lora
base_model: oopsung/llama2-7b-koNqa-test-v1
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 3aa5a43131952d0a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/3aa5a43131952d0a_train_data.json
  type:
    field_input: selftext
    field_instruction: title
    field_output: answers.text
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: ardaspear/3fa85917-ca48-4a86-9402-f6e97a492e27
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 200
micro_batch_size: 8
mlflow_experiment_name: /tmp/3aa5a43131952d0a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: d3bb3173-e665-4b1b-9fd1-359446269b92
wandb_project: Gradients-On-Five
wandb_run: your_name
wandb_runid: d3bb3173-e665-4b1b-9fd1-359446269b92
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 3fa85917-ca48-4a86-9402-f6e97a492e27

This model is a fine-tuned version of [oopsung/llama2-7b-koNqa-test-v1](https://huggingface.co/oopsung/llama2-7b-koNqa-test-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2836

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 10
- training_steps: 200

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0003 | 1    | 2.7674          |
| 2.5303        | 0.0044 | 17   | 2.5289          |
| 2.3349        | 0.0087 | 34   | 2.3943          |
| 2.3171        | 0.0131 | 51   | 2.3410          |
| 2.3498        | 0.0175 | 68   | 2.3205          |
| 2.3523        | 0.0218 | 85   | 2.3070          |
| 2.2755        | 0.0262 | 102  | 2.2987          |
| 2.3025        | 0.0305 | 119  | 2.2927          |
| 2.3064        | 0.0349 | 136  | 2.2887          |
| 2.2394        | 0.0393 | 153  | 2.2859          |
| 2.3192        | 0.0436 | 170  | 2.2842          |
| 2.3201        | 0.0480 | 187  | 2.2836          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1