metadata
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
See axolotl config
axolotl version: 0.4.0
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>"
qlora-out/v1.2
This model is a fine-tuned version of 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