Closed mellahysf closed 1 year ago
Hi @mellahysf, Thanks for your comment. The model's name is correct. You faced this issue because the code enforce to load the model from local files. We've disabled (local_files_only = True) lines (365, 374, 383, and 392) to allow the trainer to load the models from Huggingface (online). Try the code now, it should work now. Thanks
Hi,
I want to run your scripts run_trainier_seq2seq_huggingface.py but it gives me the folowing error:
last_checkpoint None 03/26/2022 14:49:11 - WARNING - main - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: False 03/26/2022 14:49:11 - INFO - main - Training/evaluation parameters Seq2SeqTrainingArguments(output_dir='/content/AraT5_FT_title_generation', overwrite_output_dir=True, do_train=True, do_eval=True, do_predict=False, evaluation_strategy=<IntervalStrategy.EPOCH: 'epoch'>, prediction_loss_only=False, per_device_train_batch_size=8, per_device_eval_batch_size=8, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=1, eval_accumulation_steps=None, learning_rate=5e-05, weight_decay=0.0, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, max_grad_norm=1.0, num_train_epochs=3.0, max_steps=-1, lr_scheduler_type=<SchedulerType.LINEAR: 'linear'>, warmup_ratio=0.0, warmup_steps=0, logging_dir='runs/Mar26_14-49-11_1f6d9e124699', logging_strategy=<IntervalStrategy.EPOCH: 'epoch'>, logging_first_step=False, logging_steps=500, save_strategy=<IntervalStrategy.STEPS: 'steps'>, save_steps=500, save_total_limit=None, no_cuda=False, seed=42, fp16=False, fp16_opt_level='O1', fp16_backend='auto', fp16_full_eval=False, local_rank=-1, tpu_num_cores=None, tpu_metrics_debug=False, debug=False, dataloader_drop_last=False, eval_steps=500, dataloader_num_workers=0, past_index=-1, run_name='/content/AraT5_FT_title_generation', disable_tqdm=False, remove_unused_columns=True, label_names=None, load_best_model_at_end=True, metric_for_best_model='eval_bleu', greater_is_better=True, ignore_data_skip=False, sharded_ddp=[], deepspeed=None, label_smoothing_factor=0.0, adafactor=False, group_by_length=False, length_column_name='length', report_to=['tensorboard'], ddp_find_unused_parameters=None, dataloader_pin_memory=True, skip_memory_metrics=False, mp_parameters='', sortish_sampler=False, predict_with_generate=True) [INFO] loading from TSV 03/26/2022 14:49:11 - WARNING - datasets.builder - Using custom data configuration default-942a41af4b2c6152 Downloading and preparing dataset csv/default to /tmp/AraT5_cache_dir/csv/default-942a41af4b2c6152/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519... Downloading data files: 100% 2/2 [00:00<00:00, 9446.63it/s] Extracting data files: 100% 2/2 [00:00<00:00, 985.16it/s] Dataset csv downloaded and prepared to /tmp/AraT5_cache_dir/csv/default-942a41af4b2c6152/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519. Subsequent calls will reuse this data. 100% 2/2 [00:00<00:00, 803.74it/s] Cannot find the requested files in the cached path and outgoing traffic has been disabled. To enable model look-ups and downloads online, set 'local_files_only' to False. Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/transformers/configuration_utils.py", line 466, in get_config_dict user_agent=user_agent, File "/usr/local/lib/python3.7/dist-packages/transformers/file_utils.py", line 1173, in cached_path local_files_only=local_files_only, File "/usr/local/lib/python3.7/dist-packages/transformers/file_utils.py", line 1383, in get_from_cache "Cannot find the requested files in the cached path and outgoing traffic has been" FileNotFoundError: Cannot find the requested files in the cached path and outgoing traffic has been disabled. To enable model look-ups and downloads online, set 'local_files_only' to False.
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "run_trainier_seq2seq_huggingface.py", line 807, in
main()
File "run_trainier_seq2seq_huggingface.py", line 365, in main
local_files_only = True
File "/usr/local/lib/python3.7/dist-packages/transformers/models/auto/configuration_auto.py", line 398, in from_pretrained
configdict, = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/transformers/configuration_utils.py", line 478, in get_config_dict
raise EnvironmentError(msg)
OSError: Can't load config for 'UBC-NLP/AraT5-base'. Make sure that:
'UBC-NLP/AraT5-base' is a correct model identifier listed on 'https://huggingface.co/models'
or 'UBC-NLP/AraT5-base' is the correct path to a directory containing a config.json file
How to fix it please?