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---
library_name: transformers
base_model: minpeter/tiny-ko-124m-base
tags:
- axolotl
- generated_from_trainer
datasets:
- lemon-mint/Korean-FineTome-100k
- lemon-mint/smol-koreantalk
- heegyu/open-korean-instructions-v20231020
- trillionlabs/multisystem-curated
- allenai/tulu-3-sft-personas-instruction-following
- coastral/korean-writing-style-instruct
- devngho/korean-instruction-mix
- youjunhyeok/Magpie-Pro-300K-Filtered-ko
- youjunhyeok/smoltalk-ko-translate
model-index:
- name: tiny-ko-124m-sft
  results: []
license: apache-2.0
---

<!-- 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: `0.11.0.dev0`
```yaml
base_model: minpeter/tiny-ko-124m-base

hub_model_id: minpeter/tiny-ko-124m-sft
output_dir: ./outputs/tiny-ko-124m-sft
wandb_project: "axolotl"
wandb_entity: "kasfiekfs-e"

model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

strict: false

chat_template: chatml
datasets:
  - path: lemon-mint/Korean-FineTome-100k
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: role
      content: content

  - path: lemon-mint/smol-koreantalk
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: role
      content: content

  - path: heegyu/open-korean-instructions-v20231020
    type: chat_template
    split: train
    field_messages: conversations
    message_property_mappings:
      role: from
      content: value
    roles:
      user: ["human", "user"]
      assistant: ["gpt", "assistant", "bot"]
      system: ["system", "input"]
  - path: trillionlabs/multisystem-curated
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: role
      content: content
  - path: allenai/tulu-3-sft-personas-instruction-following
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: role
      content: content
  - path: coastral/korean-writing-style-instruct
    type: chat_template
    split: train
    field_messages: conversations
    message_property_mappings:
      role: from
      content: value

  - path: devngho/korean-instruction-mix
    type: chat_template
    split: train
    field_messages: messages
    message_property_mappings:
      role: from
      content: value

  - path: youjunhyeok/Magpie-Pro-300K-Filtered-ko
    type: chat_template
    split: train
    field_messages: conversations
    message_property_mappings:
      role: from
      content: value

  - path: youjunhyeok/smoltalk-ko-translate
    type: chat_template
    split: train
    name: merge_filtered
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content

dataset_prepared_path: last_run_prepared
val_set_size: 0.001
save_safetensors: true
sequence_len: 2048
sample_packing: false
pad_to_sequence_len: false
use_pose: true
pose_max_context_len: 65536

overrides_of_model_config:
  rope_theta: 10000.0
  max_position_embeddings: 65536

gradient_accumulation_steps: 8
micro_batch_size: 32
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 3e-4

train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: true

gradient_checkpointing: false
gradient_checkpointing_kwargs:
  use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
sdp_attention:
s2_attention:

save_steps: 200
warmup_steps: 20
eval_steps: 200
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:

```

</details><br>

# tiny-ko-124m-sft

This model is a fine-tuned version of [minpeter/tiny-ko-124m-base](https://huggingface.co/minpeter/tiny-ko-124m-base) on the lemon-mint/Korean-FineTome-100k, the lemon-mint/smol-koreantalk, the heegyu/open-korean-instructions-v20231020, the trillionlabs/multisystem-curated, the allenai/tulu-3-sft-personas-instruction-following, the coastral/korean-writing-style-instruct, the devngho/korean-instruction-mix, the youjunhyeok/Magpie-Pro-300K-Filtered-ko and the youjunhyeok/smoltalk-ko-translate datasets.
It achieves the following results on the evaluation set:
- Loss: 1.7098

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 64
- 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: 20
- training_steps: 5042

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0      | 0    | 2.7016          |
| 2.1419        | 0.0397 | 200  | 2.1320          |
| 2.0675        | 0.0793 | 400  | 2.0446          |
| 2.0252        | 0.1190 | 600  | 1.9864          |
| 1.9304        | 0.1587 | 800  | 1.9468          |
| 1.9536        | 0.1983 | 1000 | 1.9145          |
| 1.8692        | 0.2380 | 1200 | 1.8879          |
| 1.8556        | 0.2777 | 1400 | 1.8645          |
| 1.8421        | 0.3174 | 1600 | 1.8433          |
| 1.9118        | 0.3570 | 1800 | 1.8256          |
| 1.7791        | 0.3967 | 2000 | 1.8090          |
| 1.8162        | 0.4364 | 2200 | 1.7934          |
| 1.796         | 0.4760 | 2400 | 1.7795          |
| 1.749         | 0.5157 | 2600 | 1.7661          |
| 1.7536        | 0.5554 | 2800 | 1.7540          |
| 1.7672        | 0.5950 | 3000 | 1.7432          |
| 1.7523        | 0.6347 | 3200 | 1.7336          |
| 1.7074        | 0.6744 | 3400 | 1.7259          |
| 1.7218        | 0.7141 | 3600 | 1.7202          |
| 1.6928        | 0.7537 | 3800 | 1.7158          |
| 1.7184        | 0.7934 | 4000 | 1.7127          |
| 1.761         | 0.8331 | 4200 | 1.7109          |
| 1.7481        | 0.8727 | 4400 | 1.7101          |
| 1.7245        | 0.9124 | 4600 | 1.7098          |
| 1.7076        | 0.9521 | 4800 | 1.7097          |
| 1.7403        | 0.9917 | 5000 | 1.7098          |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1