| """ |
| E2E tests for llama pretrain |
| """ |
|
|
| import logging |
| import os |
| import unittest |
|
|
| 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_model_output_exists, check_tensorboard, with_temp_dir |
|
|
| LOG = logging.getLogger("axolotl.tests.e2e") |
| os.environ["WANDB_DISABLED"] = "true" |
|
|
|
|
| class TestEmbeddingsLrScale(unittest.TestCase): |
| """ |
| Test case for embedding_lr* |
| """ |
|
|
| @with_temp_dir |
| def test_train_w_embedding_lr_scale(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "HuggingFaceTB/SmolLM2-135M", |
| "flash_attention": True, |
| "sequence_len": 1024, |
| "sample_packing": True, |
| "special_tokens": { |
| "pad_token": "<|endoftext|>", |
| }, |
| "datasets": [ |
| { |
| "path": "mhenrichsen/alpaca_2k_test", |
| "type": "alpaca", |
| }, |
| ], |
| "max_steps": 5, |
| "num_epochs": 1, |
| "micro_batch_size": 1, |
| "gradient_accumulation_steps": 1, |
| "val_set_size": 0.0, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_torch_fused", |
| "embedding_lr_scale": 0.5, |
| "lr_scheduler": "cosine", |
| "save_safetensors": True, |
| "bf16": "auto", |
| "use_tensorboard": 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_model_output_exists(temp_dir, cfg) |
|
|
| check_tensorboard( |
| temp_dir + "/runs", "train/train_loss", 2.0, "Loss is too high" |
| ) |
|
|
| @with_temp_dir |
| def test_train_w_embedding_lr(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "HuggingFaceTB/SmolLM2-135M", |
| "flash_attention": True, |
| "sequence_len": 1024, |
| "sample_packing": True, |
| "special_tokens": { |
| "pad_token": "<|endoftext|>", |
| }, |
| "datasets": [ |
| { |
| "path": "mhenrichsen/alpaca_2k_test", |
| "type": "alpaca", |
| }, |
| ], |
| "max_steps": 5, |
| "num_epochs": 1, |
| "micro_batch_size": 1, |
| "gradient_accumulation_steps": 1, |
| "val_set_size": 0.0, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_torch_fused", |
| "embedding_lr": 0.000005, |
| "lr_scheduler": "cosine", |
| "save_safetensors": True, |
| "bf16": "auto", |
| "use_tensorboard": True, |
| } |
| ) |
| normalize_config(cfg) |
| cli_args = TrainerCliArgs() |
| dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args) |
|
|
| train(cfg=cfg, dataset_meta=dataset_meta) |
| check_model_output_exists(temp_dir, cfg) |
|
|
| check_tensorboard( |
| temp_dir + "/runs", "train/train_loss", 2.0, "Loss is too high" |
| ) |
|
|
