| """ |
| E2E tests for llama |
| """ |
|
|
| import logging |
| import os |
|
|
| from e2e.utils import check_model_output_exists |
|
|
| 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 |
|
|
| LOG = logging.getLogger("axolotl.tests.e2e") |
| os.environ["WANDB_DISABLED"] = "true" |
|
|
|
|
| class TestLlama: |
| """ |
| Test case for Llama models |
| """ |
|
|
| def test_fft_trust_remote_code(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "JackFram/llama-68m", |
| "tokenizer_type": "LlamaTokenizer", |
| "trust_remote_code": True, |
| "sequence_len": 512, |
| "val_set_size": 0.1, |
| "special_tokens": { |
| "unk_token": "<unk>", |
| "bos_token": "<s>", |
| "eos_token": "</s>", |
| }, |
| "datasets": [ |
| { |
| "path": "mhenrichsen/alpaca_2k_test", |
| "type": "alpaca", |
| }, |
| ], |
| "num_epochs": 1, |
| "max_steps": 5, |
| "micro_batch_size": 2, |
| "gradient_accumulation_steps": 1, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_bnb_8bit", |
| "lr_scheduler": "cosine", |
| "flash_attention": True, |
| "sample_packing": True, |
| "bf16": True, |
| "save_safetensors": 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) |
|
|
| def test_fix_untrained_tokens(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "HuggingFaceTB/SmolLM2-135M", |
| "fix_untrained_tokens": True, |
| "sequence_len": 512, |
| "val_set_size": 0.0, |
| "special_tokens": { |
| "pad_token": "<|endoftext|>", |
| "bos_token": "<|custom_im_start|>", |
| "eos_token": "<|custom_im_end|>", |
| }, |
| "datasets": [ |
| { |
| "chat_template": "jinja", |
| "chat_template_jinja": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|custom_im_start|>' + message['role'] + '\n' + message['content'] + '<|custom_im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|custom_im_start|>assistant\n' }}{% endif %}", |
| "path": "mlabonne/FineTome-100k", |
| "type": "chat_template", |
| "split": "train[:10%]", |
| "field_messages": "conversations", |
| "message_field_role": "from", |
| "message_field_content": "value", |
| }, |
| ], |
| "num_epochs": 1, |
| "max_steps": 5, |
| "micro_batch_size": 1, |
| "gradient_accumulation_steps": 1, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_8bit", |
| "lr_scheduler": "cosine", |
| "flash_attention": True, |
| "sample_packing": True, |
| "bf16": True, |
| "save_safetensors": 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) |
|
|
| def test_fix_untrained_tokens_already_trained(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "HuggingFaceTB/SmolLM2-135M", |
| "fix_untrained_tokens": True, |
| "sequence_len": 512, |
| "val_set_size": 0.0, |
| "special_tokens": { |
| "pad_token": "<|endoftext|>", |
| }, |
| "chat_template": "chatml", |
| "datasets": [ |
| { |
| "path": "mlabonne/FineTome-100k", |
| "type": "chat_template", |
| "split": "train[:10%]", |
| "field_messages": "conversations", |
| "message_field_role": "from", |
| "message_field_content": "value", |
| }, |
| ], |
| "num_epochs": 1, |
| "max_steps": 5, |
| "micro_batch_size": 1, |
| "gradient_accumulation_steps": 1, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_8bit", |
| "lr_scheduler": "cosine", |
| "flash_attention": True, |
| "sample_packing": True, |
| "bf16": True, |
| "save_safetensors": 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) |
|
|
| def test_batch_flattening(self, temp_dir): |
| |
| cfg = DictDefault( |
| { |
| "base_model": "HuggingFaceTB/SmolLM2-135M", |
| "trust_remote_code": True, |
| "sequence_len": 512, |
| "val_set_size": 0.01, |
| "special_tokens": { |
| "pad_token": "<|endoftext|>", |
| }, |
| "datasets": [ |
| { |
| "path": "mhenrichsen/alpaca_2k_test", |
| "type": "alpaca", |
| }, |
| ], |
| "num_epochs": 1, |
| "max_steps": 5, |
| "micro_batch_size": 4, |
| "gradient_accumulation_steps": 1, |
| "output_dir": temp_dir, |
| "learning_rate": 0.00001, |
| "optimizer": "adamw_8bit", |
| "lr_scheduler": "cosine", |
| "flash_attention": True, |
| "sample_packing": False, |
| "batch_flattening": True, |
| "bf16": True, |
| "save_safetensors": 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) |
|
|
