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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 |