de8a625dd7
* [ci] make e2e tests a bit faster by reducing test split size * use 10% split of alpaca dataset to speed up dataset loading/tokenization * reduce gas 4->2 for most e2e tests * increase val set size for packing
73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
"""
|
|
E2E tests for packed training
|
|
"""
|
|
|
|
import logging
|
|
import os
|
|
import unittest
|
|
|
|
from transformers.utils import is_torch_bf16_gpu_available
|
|
|
|
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
|
|
|
|
from .utils import check_tensorboard, with_temp_dir
|
|
|
|
LOG = logging.getLogger("axolotl.tests.e2e")
|
|
os.environ["WANDB_DISABLED"] = "true"
|
|
|
|
|
|
class TestPackedLlama(unittest.TestCase):
|
|
"""
|
|
Test case for Packed training of llama models
|
|
"""
|
|
|
|
@with_temp_dir
|
|
def test_loss_packed(self, temp_dir):
|
|
# pylint: disable=duplicate-code
|
|
cfg = DictDefault(
|
|
{
|
|
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
|
"sequence_len": 1024,
|
|
"sample_packing": True,
|
|
"flash_attention": True,
|
|
"val_set_size": 0.0,
|
|
"special_tokens": {
|
|
"pad_token": "<|endoftext|>",
|
|
},
|
|
"datasets": [
|
|
{
|
|
"path": "vicgalle/alpaca-gpt4",
|
|
"type": "alpaca",
|
|
},
|
|
],
|
|
"num_epochs": 1,
|
|
"micro_batch_size": 2,
|
|
"gradient_accumulation_steps": 2,
|
|
"output_dir": temp_dir,
|
|
"learning_rate": 0.00001,
|
|
"optimizer": "adamw_torch_fused",
|
|
"lr_scheduler": "cosine",
|
|
"max_steps": 5,
|
|
"use_tensorboard": True,
|
|
}
|
|
)
|
|
if is_torch_bf16_gpu_available():
|
|
cfg.bf16 = True
|
|
else:
|
|
cfg.fp16 = 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)
|
|
|
|
check_tensorboard(
|
|
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
|
|
)
|