1d91d905c9
* remove deprecated wandb env var * remove os.environ wandb setting; unused loggers * remove os.environ wandb setting; unused loggers
129 lines
4.3 KiB
Python
129 lines
4.3 KiB
Python
"""
|
|
E2E tests for gemma2
|
|
"""
|
|
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
|
|
from axolotl.cli.args import TrainerCliArgs
|
|
from axolotl.common.datasets import load_datasets
|
|
from axolotl.train import train
|
|
from axolotl.utils.config import normalize_config, validate_config
|
|
from axolotl.utils.dict import DictDefault
|
|
|
|
|
|
class TestGemma2:
|
|
"""
|
|
Test case for Gemma2 models
|
|
"""
|
|
|
|
@pytest.mark.parametrize(
|
|
"sample_packing",
|
|
[True, False],
|
|
)
|
|
def test_lora_gemma2(self, temp_dir, sample_packing):
|
|
# pylint: disable=duplicate-code
|
|
cfg = DictDefault(
|
|
{
|
|
"base_model": "axolotl-ai-co/gemma-2-33M",
|
|
"trust_remote_code": True,
|
|
"sample_packing": sample_packing,
|
|
"flash_attention": True,
|
|
"sequence_len": 2048,
|
|
"adapter": "lora",
|
|
"lora_r": 8,
|
|
"lora_alpha": 16,
|
|
"lora_dropout": 0.05,
|
|
"lora_target_linear": True,
|
|
"val_set_size": 0,
|
|
"datasets": [
|
|
{
|
|
"path": "mlabonne/FineTome-100k",
|
|
"type": "chat_template",
|
|
"field_messages": "conversations",
|
|
"message_property_mappings": {
|
|
"role": "from",
|
|
"content": "value",
|
|
},
|
|
"drop_system_message": True,
|
|
"split": "train[:1%]",
|
|
},
|
|
],
|
|
"special_tokens": {
|
|
"bos_token": "<bos>",
|
|
"eos_token": "<eos>",
|
|
},
|
|
"chat_template": "gemma", # gemma2's template is same as gemma
|
|
"num_epochs": 1,
|
|
"micro_batch_size": 1,
|
|
"gradient_accumulation_steps": 2,
|
|
"output_dir": temp_dir,
|
|
"learning_rate": 0.00001,
|
|
"optimizer": "adamw_bnb_8bit",
|
|
"lr_scheduler": "cosine",
|
|
"max_steps": 5,
|
|
"save_safetensors": True,
|
|
"bf16": True,
|
|
}
|
|
)
|
|
cfg = validate_config(cfg)
|
|
normalize_config(cfg)
|
|
cli_args = TrainerCliArgs()
|
|
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
|
|
|
|
train(cfg=cfg, dataset_meta=dataset_meta)
|
|
assert (Path(temp_dir) / "adapter_model.safetensors").exists()
|
|
|
|
@pytest.mark.parametrize(
|
|
"sample_packing",
|
|
[True, False],
|
|
)
|
|
def test_fft_gemma2(self, temp_dir, sample_packing):
|
|
# pylint: disable=duplicate-code
|
|
cfg = DictDefault(
|
|
{
|
|
"base_model": "axolotl-ai-co/gemma-2-33M",
|
|
"trust_remote_code": True,
|
|
"sample_packing": sample_packing,
|
|
"flash_attention": True,
|
|
"sequence_len": 2048,
|
|
"val_set_size": 0,
|
|
"datasets": [
|
|
{
|
|
"path": "mlabonne/FineTome-100k",
|
|
"type": "chat_template",
|
|
"field_messages": "conversations",
|
|
"message_property_mappings": {
|
|
"role": "from",
|
|
"content": "value",
|
|
},
|
|
"split": "train[:1%]",
|
|
"drop_system_message": True,
|
|
},
|
|
],
|
|
"chat_template": "gemma", # gemma2's template is same as gemma
|
|
"special_tokens": {
|
|
"bos_token": "<bos>",
|
|
"eos_token": "<eos>",
|
|
},
|
|
"num_epochs": 1,
|
|
"micro_batch_size": 1,
|
|
"gradient_accumulation_steps": 2,
|
|
"output_dir": temp_dir,
|
|
"learning_rate": 0.00001,
|
|
"optimizer": "adamw_bnb_8bit",
|
|
"lr_scheduler": "cosine",
|
|
"max_steps": 5,
|
|
"save_safetensors": True,
|
|
"bf16": True,
|
|
}
|
|
)
|
|
cfg = validate_config(cfg)
|
|
normalize_config(cfg)
|
|
cli_args = TrainerCliArgs()
|
|
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
|
|
|
|
train(cfg=cfg, dataset_meta=dataset_meta)
|
|
assert (Path(temp_dir) / "model.safetensors").exists()
|