|
--- |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: JY623/KoSOLAR-v2.0 |
|
model-index: |
|
- name: qlora-out/v1.2 |
|
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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
|
<details><summary>See axolotl config</summary> |
|
|
|
axolotl version: `0.4.0` |
|
```yaml |
|
base_model: JY623/KoSOLAR-v2.0 |
|
model_type: AutoModelForCausalLM |
|
tokenizer_type: AutoTokenizer |
|
|
|
load_in_8bit: false |
|
load_in_4bit: true |
|
strict: false |
|
|
|
push_dataset_to_hub: |
|
datasets: |
|
- path: kyujinpy/KOR-OpenOrca-Platypus-v3 |
|
type: alpaca |
|
dataset_prepared_path: |
|
val_set_size: 0.05 |
|
output_dir: ./qlora-out/v1.2 |
|
|
|
adapter: qlora |
|
lora_model_dir: |
|
|
|
sequence_len: 4096 |
|
sample_packing: true |
|
pad_to_sequence_len: true |
|
|
|
lora_r: 32 |
|
lora_alpha: 16 |
|
lora_dropout: 0.05 |
|
lora_target_modules: |
|
lora_target_linear: true |
|
lora_fan_in_fan_out: |
|
|
|
wandb_project: |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_name: |
|
wandb_log_model: |
|
|
|
gradient_accumulation_steps: 4 |
|
micro_batch_size: 1 |
|
num_epochs: 2 |
|
optimizer: paged_adamw_32bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.0002 |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: auto |
|
fp16: |
|
tf32: false |
|
|
|
gradient_checkpointing: true |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
flash_attention: false |
|
|
|
warmup_steps: 20 |
|
evals_per_epoch: 4 |
|
eval_table_size: |
|
saves_per_epoch: 1 |
|
debug: |
|
deepspeed: |
|
weight_decay: 0.1 |
|
fsdp: |
|
fsdp_config: |
|
special_tokens: |
|
bos_token: "<s>" |
|
eos_token: "</s>" |
|
unk_token: "<unk>" |
|
``` |
|
|
|
</details><br> |
|
|
|
# qlora-out/v1.2 |
|
|
|
This model is a fine-tuned version of [JY623/KoSOLAR-v2.0](https://huggingface.co/JY623/KoSOLAR-v2.0) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 5.1419 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 7 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 28 |
|
- total_eval_batch_size: 7 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 20 |
|
- num_epochs: 2 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 13.4775 | 0.0 | 1 | 13.4330 | |
|
| 6.9219 | 0.25 | 64 | 6.2022 | |
|
| 5.5416 | 0.5 | 128 | 5.2780 | |
|
| 5.4282 | 0.75 | 192 | 5.1929 | |
|
| 5.4864 | 1.0 | 256 | 5.1416 | |
|
| 5.2877 | 1.24 | 320 | 5.1441 | |
|
| 5.1731 | 1.49 | 384 | 5.1413 | |
|
| 5.6221 | 1.74 | 448 | 5.1406 | |
|
| 5.3737 | 1.99 | 512 | 5.1419 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.9.0 |
|
- Transformers 4.40.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.0 |
