---
library_name: peft
base_model: Korabbit/llama-2-ko-7b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
  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: Korabbit/llama-2-ko-7b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - d6b44a0c297f4d53_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/d6b44a0c297f4d53_train_data.json
  type:
    field_input: disease
    field_instruction: catalyst
    field_output: stage
    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: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik2987/352cbfe1-34a5-448e-9702-bb0ff1c2125b
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GiB
max_steps: 25
micro_batch_size: 2
mlflow_experiment_name: /tmp/d6b44a0c297f4d53_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 5
save_strategy: steps
sequence_len: 2028
special_tokens:
  pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 352cbfe1-34a5-448e-9702-bb0ff1c2125b

This model is a fine-tuned version of [Korabbit/llama-2-ko-7b](https://huggingface.co/Korabbit/llama-2-ko-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1298

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 10
- training_steps: 25

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.5544        | 0.0051 | 1    | 3.5220          |
| 3.3707        | 0.0152 | 3    | 3.4257          |
| 3.0358        | 0.0304 | 6    | 2.2252          |
| 1.4471        | 0.0456 | 9    | 1.0823          |
| 0.3012        | 0.0608 | 12   | 0.1744          |
| 0.2963        | 0.0760 | 15   | 0.1155          |
| 0.1333        | 0.0912 | 18   | 0.1238          |
| 0.056         | 0.1064 | 21   | 0.1304          |
| 0.0073        | 0.1216 | 24   | 0.1298          |


### Framework versions

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