01/04/2024 10:04:05 - WARNING - llmtuner.model.parser - `ddp_find_unused_parameters` needs to be set as False for LoRA in DDP training. [INFO|training_args.py:1838] 2024-01-04 10:04:05,581 >> PyTorch: setting up devices /home/hangyu5/anaconda3/envs/llama_factory/lib/python3.11/site-packages/transformers/training_args.py:1751: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_token` instead. warnings.warn( 01/04/2024 10:04:05 - INFO - llmtuner.model.parser - Process rank: 0, device: cuda:0, n_gpu: 1 distributed training: True, compute dtype: None 01/04/2024 10:04:05 - INFO - llmtuner.model.parser - Training/evaluation parameters Seq2SeqTrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, auto_find_batch_size=False, bf16=False, bf16_full_eval=False, data_seed=None, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_persistent_workers=False, dataloader_pin_memory=True, ddp_backend=None, ddp_broadcast_buffers=None, ddp_bucket_cap_mb=None, ddp_find_unused_parameters=False, ddp_timeout=1800, debug=[], deepspeed=None, disable_tqdm=False, dispatch_batches=None, do_eval=False, do_predict=True, do_train=False, eval_accumulation_steps=None, eval_delay=0, eval_steps=None, evaluation_strategy=IntervalStrategy.NO, fp16=False, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, fsdp=[], fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False}, fsdp_min_num_params=0, fsdp_transformer_layer_cls_to_wrap=None, full_determinism=False, generation_config=None, generation_max_length=None, generation_num_beams=None, gradient_accumulation_steps=1, gradient_checkpointing=False, gradient_checkpointing_kwargs=None, greater_is_better=None, group_by_length=False, half_precision_backend=auto, hub_always_push=False, hub_model_id=None, hub_private_repo=False, hub_strategy=HubStrategy.EVERY_SAVE, hub_token=, ignore_data_skip=False, include_inputs_for_metrics=False, include_num_input_tokens_seen=False, include_tokens_per_second=False, jit_mode_eval=False, label_names=None, label_smoothing_factor=0.0, learning_rate=5e-05, length_column_name=length, load_best_model_at_end=False, local_rank=0, log_level=passive, log_level_replica=warning, log_on_each_node=True, logging_dir=./models/sft/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1-lora/Predict_20/runs/Jan04_10-04-05_yhyu13fuwuqi, logging_first_step=False, logging_nan_inf_filter=True, logging_steps=500, logging_strategy=IntervalStrategy.STEPS, lr_scheduler_kwargs={}, lr_scheduler_type=SchedulerType.LINEAR, max_grad_norm=1.0, max_steps=-1, metric_for_best_model=None, mp_parameters=, neftune_noise_alpha=None, no_cuda=False, num_train_epochs=3.0, optim=OptimizerNames.ADAMW_TORCH, optim_args=None, output_dir=./models/sft/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1-lora/Predict_20, overwrite_output_dir=False, past_index=-1, per_device_eval_batch_size=1, per_device_train_batch_size=8, predict_with_generate=True, prediction_loss_only=False, push_to_hub=False, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=, ray_scope=last, remove_unused_columns=True, report_to=['tensorboard'], resume_from_checkpoint=None, run_name=./models/sft/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1-lora/Predict_20, save_on_each_node=False, save_only_model=False, save_safetensors=True, save_steps=500, save_strategy=IntervalStrategy.STEPS, save_total_limit=None, seed=42, skip_memory_metrics=True, sortish_sampler=False, split_batches=False, tf32=None, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, torchdynamo=None, tpu_metrics_debug=False, tpu_num_cores=None, use_cpu=False, use_ipex=False, use_legacy_prediction_loop=False, use_mps_device=False, warmup_ratio=0.0, warmup_steps=0, weight_decay=0.0, ) 01/04/2024 10:04:05 - INFO - llmtuner.data.loader - Loading dataset ./glaive-function-calling-v2/simple-function-calling-v2_converted.json... 01/04/2024 10:04:05 - WARNING - llmtuner.data.utils - Checksum failed: missing SHA-1 hash value in dataset_info.json. Using custom data configuration default-b024aadef2a1493c Loading Dataset Infos from /home/hangyu5/anaconda3/envs/llama_factory/lib/python3.11/site-packages/datasets/packaged_modules/json Overwrite dataset info from restored data version if exists. Loading Dataset info from /home/hangyu5/.cache/huggingface/datasets/json/default-b024aadef2a1493c/0.0.0/8bb11242116d547c741b2e8a1f18598ffdd40a1d4f2a2872c7a28b697434bc96 Found cached dataset json (/home/hangyu5/.cache/huggingface/datasets/json/default-b024aadef2a1493c/0.0.0/8bb11242116d547c741b2e8a1f18598ffdd40a1d4f2a2872c7a28b697434bc96) Loading Dataset info from /home/hangyu5/.cache/huggingface/datasets/json/default-b024aadef2a1493c/0.0.0/8bb11242116d547c741b2e8a1f18598ffdd40a1d4f2a2872c7a28b697434bc96 [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file vocab.json [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file merges.txt [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file added_tokens.json [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file special_tokens_map.json [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file tokenizer_config.json [INFO|tokenization_utils_base.py:2024] 2024-01-04 10:04:06,381 >> loading file tokenizer.json [WARNING|logging.py:314] 2024-01-04 10:04:06,448 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. [INFO|configuration_utils.py:737] 2024-01-04 10:04:06,448 >> loading configuration file cognitivecomputations/dolphin-2_6-phi-2/config.json [INFO|configuration_utils.py:737] 2024-01-04 10:04:06,449 >> loading configuration file cognitivecomputations/dolphin-2_6-phi-2/config.json [INFO|configuration_utils.py:802] 2024-01-04 10:04:06,450 >> Model config PhiConfig { "_name_or_path": "cognitivecomputations/dolphin-2_6-phi-2", "activation_function": "gelu_new", "architectures": [ "PhiForCausalLM" ], "attn_pdrop": 0.0, "auto_map": { "AutoConfig": "configuration_phi.PhiConfig", "AutoModelForCausalLM": "modeling_phi.PhiForCausalLM" }, "embd_pdrop": 0.0, "flash_attn": false, "flash_rotary": false, "fused_dense": false, "img_processor": null, "initializer_range": 0.02, "layer_norm_epsilon": 1e-05, "model_type": "phi-msft", "n_embd": 2560, "n_head": 32, "n_head_kv": null, "n_inner": null, "n_layer": 32, "n_positions": 2048, "resid_pdrop": 0.1, "rotary_dim": 32, "tie_word_embeddings": false, "torch_dtype": "float16", "transformers_version": "4.36.2", "use_cache": false, "vocab_size": 51200 } [INFO|modeling_utils.py:3341] 2024-01-04 10:04:06,482 >> loading weights file cognitivecomputations/dolphin-2_6-phi-2/model.safetensors.index.json [INFO|configuration_utils.py:826] 2024-01-04 10:04:06,483 >> Generate config GenerationConfig { "use_cache": false } [INFO|configuration_utils.py:826] 2024-01-04 10:04:06,483 >> Generate config GenerationConfig { "use_cache": false } Loading checkpoint shards: 0%| | 0/2 [00:00> Some weights of the model checkpoint at ./models/dolphin-2_6-phi-2 were not used when initializing PhiForCausalLM: ['lm_head.linear.lora_B.default.weight', 'lm_head.linear.lora_A.default.weight'] - This IS expected if you are initializing PhiForCausalLM from the checkpoint of a modelcognitivecomputations/dolphin-2_6-phi-2r with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). - This IS NOT expected if you are initializing PhiForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). [INFO|modeling_utils.py:4193] 2024-01-04 10:04:07,704 >> All the weights of PhiForCausalLM were initialized from the model checkpoint at ./models/dolphin-2_6-phi-2. If your task is similar to the task the model of the checkpoint was trained on, you can already use PhiForCausalLM for predictions without further training. [INFO|configuration_utils.py:779] 2024-01-04 10:04:07,707 >> loading configuration file ./models/dolphin-2_6-phi-2/generation_config.json [INFO|configuration_utils.py:826] 2024-01-04 10:04:07,707 >> Generate config GenerationConfig {} 01/04/2024 10:04:08 - INFO - llmtuner.model.adapter - Fine-tuning method: LoRA 01/04/2024 10:04:09 - INFO - llmtuner.model.adapter - Merged 1 adapter(s). 01/04/2024 10:04:09 - INFO - llmtuner.model.adapter - Loaded adapter(s): ./models/sft/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1-lora 01/04/2024 10:04:09 - INFO - llmtuner.model.loader - trainable params: 0 || all params: 2779683840 || trainable%: 0.0000 01/04/2024 10:04:09 - INFO - llmtuner.model.loader - This IS expected that the trainable params is 0 if you are using model for inference only. Running tokenizer on dataset: 0%| | 0/20 [00:00> PyTorch: setting up devices [INFO|trainer.py:3166] 2024-01-04 10:04:10,639 >> ***** Running Prediction ***** [INFO|trainer.py:3168] 2024-01-04 10:04:10,639 >> Num examples = 20 [INFO|trainer.py:3171] 2024-01-04 10:04:10,639 >> Batch size = 1 [INFO|configuration_utils.py:826] 2024-01-04 10:04:10,651 >> Generate config GenerationConfig { "use_cache": false } /home/hangyu5/anaconda3/envs/llama_factory/lib/python3.11/site-packages/transformers/generation/utils.py:1518: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use and modify the model generation configuration (see https://huggingface.co/docs/transformers/generation_strategies#default-text-generation-configuration ) warnings.warn( input_ids: [32, 8537, 1022, 257, 11040, 2836, 290, 281, 11666, 4430, 8796, 13, 383, 8796, 3607, 7613, 11, 6496, 11, 290, 23507, 7429, 284, 262, 2836, 338, 2683, 13, 198, 20490, 25, 36230, 25, 921, 389, 257, 7613, 8796, 351, 1895, 284, 262, 1708, 5499, 13, 5765, 606, 611, 2672, 532, 198, 90, 198, 50284, 1, 3672, 1298, 366, 1136, 62, 1069, 3803, 62, 4873, 1600, 198, 50284, 1, 11213, 1298, 366, 3855, 262, 5163, 2494, 1022, 734, 19247, 1600, 198, 50284, 1, 17143, 7307, 1298, 1391, 198, 50280, 1, 4906, 1298, 366, 15252, 1600, 198, 50280, 1, 48310, 1298, 1391, 198, 50276, 1, 8692, 62, 34415, 1298, 1391, 198, 50272, 1, 4906, 1298, 366, 8841, 1600, 198, 50272, 1, 11213, 1298, 366, 464, 7395, 284, 10385, 422, 1, 198, 50276, 5512, 198, 50276, 1, 16793, 62, 34415, 1298, 1391, 198, 50272, 1, 4906, 1298, 366, 8841, 1600, 198, 50272, 1, 11213, 1298, 366, 464, 7395, 284, 10385, 284, 1, 198, 50276, 92, 198, 50280, 5512, 198, 50280, 1, 35827, 1298, 685, 198, 50276, 1, 8692, 62, 34415, 1600, 198, 50276, 1, 16793, 62, 34415, 1, 198, 50280, 60, 198, 50284, 92, 198, 92, 198, 198, 6090, 345, 1492, 257, 5474, 329, 502, 422, 968, 1971, 284, 3576, 30, 198, 48902, 25] inputs: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. Human: SYSTEM: You are a helpful assistant with access to the following functions. Use them if required - { "name": "get_exchange_rate", "description": "Get the exchange rate between two currencies", "parameters": { "type": "object", "properties": { "base_currency": { "type": "string", "description": "The currency to convert from" }, "target_currency": { "type": "string", "description": "The currency to convert to" } }, "required": [ "base_currency", "target_currency" ] } } Can you book a flight for me from New York to London? Assistant: 0%| | 0/20 [00:00