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classification1788518.out

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+Loading pytorch-gpu/py3/2.1.1
+  Loading requirement: cuda/11.8.0 nccl/2.18.5-1-cuda cudnn/8.7.0.84-cuda
+    gcc/8.5.0 openmpi/4.1.5-cuda intel-mkl/2020.4 magma/2.7.1-cuda sox/14.4.2
+    sparsehash/2.0.3 libjpeg-turbo/2.1.3 ffmpeg/4.4.4
++ HF_DATASETS_OFFLINE=1
++ TRANSFORMERS_OFFLINE=1
++ python3 deberta_training_multi.py
+train:
+DatasetInfo(description='', citation='', homepage='', license='', features={'metadata': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), '1_legislation': Value(dtype='int64', id=None), '10_journaux': Value(dtype='int64', id=None), '12_presentations': Value(dtype='int64', id=None), '13_lettres': Value(dtype='int64', id=None), '2_rapport_evaluation': Value(dtype='int64', id=None), '3_rapport_comptes': Value(dtype='int64', id=None), '4_rapport_activite': Value(dtype='int64', id=None), '5_rapport_risque': Value(dtype='int64', id=None), '6_plan': Value(dtype='int64', id=None), '7_charte': Value(dtype='int64', id=None), '__index_level_0__': Value(dtype='int64', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name=None, dataset_name=None, config_name=None, version=None, splits=None, download_checksums=None, download_size=None, post_processing_size=None, dataset_size=None, size_in_bytes=None)
+test:
+DatasetInfo(description='', citation='', homepage='', license='', features={'metadata': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), '1_legislation': Value(dtype='int64', id=None), '10_journaux': Value(dtype='int64', id=None), '12_presentations': Value(dtype='int64', id=None), '13_lettres': Value(dtype='int64', id=None), '2_rapport_evaluation': Value(dtype='int64', id=None), '3_rapport_comptes': Value(dtype='int64', id=None), '4_rapport_activite': Value(dtype='int64', id=None), '5_rapport_risque': Value(dtype='int64', id=None), '6_plan': Value(dtype='int64', id=None), '7_charte': Value(dtype='int64', id=None), '__index_level_0__': Value(dtype='int64', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name=None, dataset_name=None, config_name=None, version=None, splits=None, download_checksums=None, download_size=None, post_processing_size=None, dataset_size=None, size_in_bytes=None)
+validation:
+DatasetInfo(description='', citation='', homepage='', license='', features={'metadata': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), '1_legislation': Value(dtype='int64', id=None), '10_journaux': Value(dtype='int64', id=None), '12_presentations': Value(dtype='int64', id=None), '13_lettres': Value(dtype='int64', id=None), '2_rapport_evaluation': Value(dtype='int64', id=None), '3_rapport_comptes': Value(dtype='int64', id=None), '4_rapport_activite': Value(dtype='int64', id=None), '5_rapport_risque': Value(dtype='int64', id=None), '6_plan': Value(dtype='int64', id=None), '7_charte': Value(dtype='int64', id=None), '__index_level_0__': Value(dtype='int64', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name=None, dataset_name=None, config_name=None, version=None, splits=None, download_checksums=None, download_size=None, post_processing_size=None, dataset_size=None, size_in_bytes=None)
+/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/convert_slow_tokenizer.py:515: UserWarning: The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option which is not implemented in the fast tokenizers. In practice this means that the fast version of the tokenizer can produce unknown tokens whereas the sentencepiece version would have converted these unknown tokens into a sequence of byte tokens matching the original piece of text.
+  warnings.warn(
+
+
+
+/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
+  return self.fget.__get__(instance, owner)()
+Some weights of DebertaV2ForSequenceClassification were not initialized from the model checkpoint at deberta-large and are newly initialized: ['classifier.bias', 'classifier.weight', 'pooler.dense.bias', 'pooler.dense.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+comet_ml is installed but `COMET_API_KEY` is not set.
+Using the `WANDB_DISABLED` environment variable is deprecated and will be removed in v5. Use the --report_to flag to control the integrations used for logging result (for instance --report_to none).
+Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
+2024/05/06 14:31:40 WARNING mlflow.utils.git_utils: Failed to import Git (the Git executable is probably not on your PATH), so Git SHA is not available. Error: Failed to initialize: Bad git executable.
+The git executable must be specified in one of the following ways:
+    - be included in your $PATH
+    - be set via $GIT_PYTHON_GIT_EXECUTABLE
+    - explicitly set via git.refresh()
+
+All git commands will error until this is rectified.
+
+This initial warning can be silenced or aggravated in the future by setting the
+$GIT_PYTHON_REFRESH environment variable. Use one of the following values:
+    - quiet|q|silence|s|none|n|0: for no warning or exception
+    - warn|w|warning|1: for a printed warning
+    - error|e|raise|r|2: for a raised exception
+
+Example:
+    export GIT_PYTHON_REFRESH=quiet
+
+COMET WARNING: Can not parse empty Comet API key
+COMET INFO: No Comet API Key was found, creating an OfflineExperiment. Set up your API Key to get the full Comet experience https://www.comet.com/docs/python-sdk/advanced/#python-configuration
+COMET WARNING: Can not parse empty Comet API key
+COMET WARNING: To get all data logged automatically, import comet_ml before the following modules: sklearn, torch.
+COMET INFO: Using '/gpfsdswork/projects/rech/fmr/uft12cr/classification/.cometml-runs' path as offline directory. Pass 'offline_directory' parameter into constructor or set the 'COMET_OFFLINE_DIRECTORY' environment variable to manually choose where to store offline experiment archives.
+huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
+To disable this warning, you can either:
+	- Avoid using `tokenizers` before the fork if possible
+	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
+huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
+To disable this warning, you can either:
+	- Avoid using `tokenizers` before the fork if possible
+	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
+COMET INFO: Couldn't find a Git repository in '/gpfsdswork/projects/rech/fmr/uft12cr/classification' nor in any parent directory. Set `COMET_GIT_DIRECTORY` if your Git Repository is elsewhere.
+
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+
+  File "/gpfsdswork/projects/rech/fmr/uft12cr/classification/deberta_training_multi.py", line 138, in <module>
+    trainer.train()
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/trainer.py", line 1561, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/trainer.py", line 1968, in _inner_training_loop
+    self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/trainer.py", line 2329, in _maybe_log_save_evaluate
+    metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)
+              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/trainer.py", line 3136, in evaluate
+    output = eval_loop(
+             ^^^^^^^^^^
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/transformers/trainer.py", line 3427, in evaluation_loop
+    metrics = self.compute_metrics(EvalPrediction(predictions=all_preds, label_ids=all_labels))
+              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/gpfsdswork/projects/rech/fmr/uft12cr/classification/deberta_training_multi.py", line 124, in compute_metrics
+    result = multi_label_metrics(
+             ^^^^^^^^^^^^^^^^^^^^
+  File "/gpfsdswork/projects/rech/fmr/uft12cr/classification/deberta_training_multi.py", line 102, in multi_label_metrics
+    metrics_per_label = precision_recall_fscore_support(labels, y_pred, average=None)
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+NameError: name 'precision_recall_fscore_support' is not defined
+
+
+COMET INFO: Comet.ml OfflineExperiment Summary
+COMET INFO: ---------------------------------------------------------------------------------------
+COMET INFO:   Data:
+COMET INFO:     display_summary_level : 1
+COMET INFO:     name                  : deberta-classification-dila
+COMET INFO:     url                   : [OfflineExperiment will get URL after upload]
+COMET INFO:   Others:
+COMET INFO:     Created from       : MLFlow auto-logger
+COMET INFO:     Name               : deberta-classification-dila
+COMET INFO:     offline_experiment : True
+COMET INFO:   Parameters:
+COMET INFO:     _name_or_path                      : deberta-large
+COMET INFO:     adafactor                          : False
+COMET INFO:     adam_beta1                         : 0.9
+COMET INFO:     adam_beta2                         : 0.999
+COMET INFO:     adam_epsilon                       : 1e-08
+COMET INFO:     add_cross_attention                : False
+COMET INFO:     architectures                      : None
+COMET INFO:     attention_probs_dropout_prob       : 0.1
+COMET INFO:     auto_find_batch_size               : False
+COMET INFO:     bad_words_ids                      : None
+COMET INFO:     begin_suppress_tokens              : None
+COMET INFO:     bf16                               : False
+COMET INFO:     bf16_full_eval                     : False
+COMET INFO:     bos_token_id                       : None
+COMET INFO:     chunk_size_feed_forward            : 0
+COMET INFO:     cross_attention_hidden_size        : None
+COMET INFO:     data_seed                          : None
+COMET INFO:     dataloader_drop_last               : False
+COMET INFO:     dataloader_num_workers             : 0
+COMET INFO:     dataloader_persistent_workers      : False
+COMET INFO:     dataloader_pin_memory              : True
+COMET INFO:     dataloader_prefetch_factor         : None
+COMET INFO:     ddp_backend                        : None
+COMET INFO:     ddp_broadcast_buffers              : None
+COMET INFO:     ddp_bucket_cap_mb                  : None
+COMET INFO:     ddp_find_unused_parameters         : None
+COMET INFO:     ddp_timeout                        : 1800
+COMET INFO:     debug                              : []
+COMET INFO:     decoder_start_token_id             : None
+COMET INFO:     deepspeed                          : None
+COMET INFO:     disable_tqdm                       : False
+COMET INFO:     dispatch_batches                   : None
+COMET INFO:     diversity_penalty                  : 0.0
+COMET INFO:     do_eval                            : True
+COMET INFO:     do_predict                         : False
+COMET INFO:     do_sample                          : False
+COMET INFO:     do_train                           : False
+COMET INFO:     early_stopping                     : False
+COMET INFO:     encoder_no_repeat_ngram_size       : 0
+COMET INFO:     eos_token_id                       : None
+COMET INFO:     eval_accumulation_steps            : None
+COMET INFO:     eval_delay                         : 0
+COMET INFO:     eval_steps                         : None
+COMET INFO:     evaluation_strategy                : epoch
+COMET INFO:     exponential_decay_length_penalty   : None
+COMET INFO:     finetuning_task                    : None
+COMET INFO:     forced_bos_token_id                : None
+COMET INFO:     forced_eos_token_id                : None
+COMET INFO:     fp16                               : False
+COMET INFO:     fp16_backend                       : auto
+COMET INFO:     fp16_full_eval                     : False
+COMET INFO:     fp16_opt_level                     : O1
+COMET INFO:     fsdp                               : []
+COMET INFO:     fsdp_config                        : {"min_num_params": 0, "xla": false, "xla_fsdp_grad_ckpt": false}
+COMET INFO:     fsdp_min_num_params                : 0
+COMET INFO:     fsdp_transformer_layer_cls_to_wrap : None
+COMET INFO:     full_determinism                   : False
+COMET INFO:     gradient_accumulation_steps        : 1
+COMET INFO:     gradient_checkpointing             : False
+COMET INFO:     gradient_checkpointing_kwargs      : None
+COMET INFO:     greater_is_better                  : True
+COMET INFO:     group_by_length                    : False
+COMET INFO:     half_precision_backend             : auto
+COMET INFO:     hidden_act                         : gelu
+COMET INFO:     hidden_dropout_prob                : 0.1
+COMET INFO:     hidden_size                        : 768
+COMET INFO:     hub_always_push                    : False
+COMET INFO:     hub_model_id                       : None
+COMET INFO:     hub_private_repo                   : False
+COMET INFO:     hub_strategy                       : every_save
+COMET INFO:     hub_token                          : <HUB_TOKEN>
+COMET INFO:     id2label                           : {"0": "1_legislation", "1": "10_journaux", "2": "12_presentations", "3": "13_lettres", "4": "2_rapport_evaluation", "5": "3_rapport_comptes", "6": "4_rapport_activite", "7": "5_rapport_risque", "8": "6_plan", "9": "7_charte", "10": "__index_level_0__"}
+COMET INFO:     ignore_data_skip                   : False
+COMET INFO:     include_inputs_for_metrics         : False
+COMET INFO:     include_num_input_tokens_seen      : False
+COMET INFO:     include_tokens_per_second          : False
+COMET INFO:     initializer_range                  : 0.02
+COMET INFO:     intermediate_size                  : 3072
+COMET INFO:     is_decoder                         : False
+COMET INFO:     is_encoder_decoder                 : False
+COMET INFO:     jit_mode_eval                      : False
+COMET INFO:     label2id                           : {"10_journaux": 1, "12_presentations": 2, "13_lettres": 3, "1_legislation": 0, "2_rapport_evaluation": 4, "3_rapport_comptes": 5, "4_rapport_activite": 6, "5_rapport_risque": 7, "6_plan": 8, "7_charte": 9, "__index_level_0__": 10}
+COMET INFO:     label_names                        : None
+COMET INFO:     label_smoothing_factor             : 0.0
+COMET INFO:     layer_norm_eps                     : 1e-07
+COMET INFO:     learning_rate                      : 1e-05
+COMET INFO:     length_column_name                 : length
+COMET INFO:     length_penalty                     : 1.0
+COMET INFO:     load_best_model_at_end             : True
+COMET INFO:     local_rank                         : 0
+COMET INFO:     log_level                          : passive
+COMET INFO:     log_level_replica                  : warning
+COMET INFO:     log_on_each_node                   : True
+COMET INFO:     logging_dir                        : deberta-classification-dila/runs/May06_14-31-32_r6i2n2
+COMET INFO:     logging_first_step                 : False
+COMET INFO:     logging_nan_inf_filter             : True
+COMET INFO:     logging_steps                      : 500
+COMET INFO:     logging_strategy                   : steps
+COMET INFO:     lr_scheduler_kwargs                : {}
+COMET INFO:     lr_scheduler_type                  : linear
+COMET INFO:     max_grad_norm                      : 1.0
+COMET INFO:     max_length                         : 20
+COMET INFO:     max_position_embeddings            : 512
+COMET INFO:     max_relative_positions             : -1
+COMET INFO:     max_steps                          : -1
+COMET INFO:     metric_for_best_model              : f1
+COMET INFO:     min_length                         : 0
+COMET INFO:     model_type                         : deberta-v2
+COMET INFO:     mp_parameters                      : 
+COMET INFO:     neftune_noise_alpha                : None
+COMET INFO:     no_cuda                            : False
+COMET INFO:     no_repeat_ngram_size               : 0
+COMET INFO:     norm_rel_ebd                       : layer_norm
+COMET INFO:     num_attention_heads                : 12
+COMET INFO:     num_beam_groups                    : 1
+COMET INFO:     num_beams                          : 1
+COMET INFO:     num_hidden_layers                  : 12
+COMET INFO:     num_return_sequences               : 1
+COMET INFO:     num_train_epochs                   : 4
+COMET INFO:     optim                              : adamw_torch
+COMET INFO:     optim_args                         : None
+COMET INFO:     output_attentions                  : False
+COMET INFO:     output_dir                         : deberta-classification-dila
+COMET INFO:     output_hidden_states               : False
+COMET INFO:     output_scores                      : False
+COMET INFO:     overwrite_output_dir               : False
+COMET INFO:     pad_token_id                       : 0
+COMET INFO:     past_index                         : -1
+COMET INFO:     per_device_eval_batch_size         : 8
+COMET INFO:     per_device_train_batch_size        : 8
+COMET INFO:     per_gpu_eval_batch_size            : None
+COMET INFO:     per_gpu_train_batch_size           : None
+COMET INFO:     pooler_dropout                     : 0
+COMET INFO:     pooler_hidden_act                  : gelu
+COMET INFO:     pooler_hidden_size                 : 768
+COMET INFO:     pos_att_type                       : ['p2c', 'c2p']
+COMET INFO:     position_biased_input              : False
+COMET INFO:     position_buckets                   : 256
+COMET INFO:     prediction_loss_only               : False
+COMET INFO:     prefix                             : None
+COMET INFO:     problem_type                       : multi_label_classification
+COMET INFO:     pruned_heads                       : {}
+COMET INFO:     push_to_hub                        : False
+COMET INFO:     push_to_hub_model_id               : None
+COMET INFO:     push_to_hub_organization           : None
+COMET INFO:     push_to_hub_token                  : <PUSH_TO_HUB_TOKEN>
+COMET INFO:     ray_scope                          : last
+COMET INFO:     relative_attention                 : True
+COMET INFO:     remove_invalid_values              : False
+COMET INFO:     remove_unused_columns              : True
+COMET INFO:     repetition_penalty                 : 1.0
+COMET INFO:     report_to                          : ['mlflow', 'tensorboard']
+COMET INFO:     resume_from_checkpoint             : None
+COMET INFO:     return_dict                        : True
+COMET INFO:     return_dict_in_generate            : False
+COMET INFO:     run_name                           : deberta-classification-dila
+COMET INFO:     save_on_each_node                  : False
+COMET INFO:     save_only_model                    : False
+COMET INFO:     save_safetensors                   : True
+COMET INFO:     save_steps                         : 500
+COMET INFO:     save_strategy                      : epoch
+COMET INFO:     save_total_limit                   : None
+COMET INFO:     seed                               : 42
+COMET INFO:     sep_token_id                       : None
+COMET INFO:     share_att_key                      : True
+COMET INFO:     skip_memory_metrics                : True
+COMET INFO:     split_batches                      : False
+COMET INFO:     suppress_tokens                    : None
+COMET INFO:     task_specific_params               : None
+COMET INFO:     temperature                        : 1.0
+COMET INFO:     tf32                               : None
+COMET INFO:     tf_legacy_loss                     : False
+COMET INFO:     tie_encoder_decoder                : False
+COMET INFO:     tie_word_embeddings                : True
+COMET INFO:     tokenizer_class                    : None
+COMET INFO:     top_k                              : 50
+COMET INFO:     top_p                              : 1.0
+COMET INFO:     torch_compile                      : False
+COMET INFO:     torch_compile_backend              : None
+COMET INFO:     torch_compile_mode                 : None
+COMET INFO:     torch_dtype                        : None
+COMET INFO:     torchdynamo                        : None
+COMET INFO:     torchscript                        : False
+COMET INFO:     tpu_metrics_debug                  : False
+COMET INFO:     tpu_num_cores                      : None
+COMET INFO:     transformers_version               : 4.38.0.dev0
+COMET INFO:     type_vocab_size                    : 0
+COMET INFO:     typical_p                          : 1.0
+COMET INFO:     use_bfloat16                       : False
+COMET INFO:     use_cpu                            : False
+COMET INFO:     use_ipex                           : False
+COMET INFO:     use_legacy_prediction_loop         : False
+COMET INFO:     use_mps_device                     : False
+COMET INFO:     vocab_size                         : 251000
+COMET INFO:     warmup_ratio                       : 0.0
+COMET INFO:     warmup_steps                       : 0
+COMET INFO:     weight_decay                       : 0.01
+COMET INFO:   Uploads:
+COMET INFO:     conda-environment-definition : 1
+COMET INFO:     conda-info                   : 1
+COMET INFO:     conda-specification          : 1
+COMET INFO:     environment details          : 1
+COMET INFO:     filename                     : 1
+COMET INFO:     installed packages           : 1
+COMET INFO:     source_code                  : 1 (4.46 KB)
+COMET INFO: 
+COMET WARNING: To get all data logged automatically, import comet_ml before the following modules: sklearn, torch.
+COMET INFO: Still saving offline stats to messages file before program termination (may take up to 120 seconds)
+COMET INFO: Starting saving the offline archive
+COMET INFO: To upload this offline experiment, run:
+    comet upload /gpfsdswork/projects/rech/fmr/uft12cr/classification/.cometml-runs/a7c8e67565944e0b877cc72ae9023b53.zip
+Exception ignored in: <function tqdm.__del__ at 0x150062d53880>
+Traceback (most recent call last):
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/std.py", line 1149, in __del__
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/std.py", line 1303, in close
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/std.py", line 1496, in display
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/std.py", line 1152, in __str__
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/std.py", line 1454, in format_dict
+  File "/linkhome/rech/genrug01/uft12cr/.local/lib/python3.11/site-packages/tqdm/utils.py", line 335, in _screen_shape_linux
+  File "<frozen importlib._bootstrap>", line 1173, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 170, in __enter__
+  File "<frozen importlib._bootstrap>", line 196, in _get_module_lock
+  File "<frozen importlib._bootstrap>", line 72, in __init__
+TypeError: 'NoneType' object is not callable
+
+