Training in progress, epoch 1

config.json

@@ -1,9 +1,11 @@
 {
-  "_name_or_path": "mmukh/SOBertBase",
+  "_name_or_path": "lanwuwei/BERTOverflow_stackoverflow_github",
+  "_num_labels": 51,
   "architectures": [
-    "MegatronBertForSequenceClassification"
+    "BertForSequenceClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
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   "hidden_act": "gelu",
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   "hidden_size": 768,
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   "num_attention_heads": 12,
   "num_hidden_layers": 12,
+  "output_hidden_states": true,
+  "output_past": true,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "problem_type": "single_label_classification",
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   "transformers_version": "4.39.3",
   "type_vocab_size": 2,
   "use_cache": true,
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+  "vocab_size": 82000
 }

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "BertTokenizer",
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+}

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wandb/run-20240410_155650-albqrbhg/files/config.yaml

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wandb/run-20240410_155650-albqrbhg/files/output.log

@@ -0,0 +1,87 @@
+Some weights of BertForSequenceClassification were not initialized from the model checkpoint at lanwuwei/BERTOverflow_stackoverflow_github and are newly initialized: ['classifier.bias', 'classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
+dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
+  warnings.warn(
+Some weights of BertForSequenceClassification were not initialized from the model checkpoint at lanwuwei/BERTOverflow_stackoverflow_github and are newly initialized: ['classifier.bias', 'classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+{'Documentation Replication on Other Examples': 0, 'Requesting (Additional) Resources': 1, 'Inadequate Examples': 2, 'Documentation Ambiguity': 3, 'Documentation Completeness': 4, 'Lack of Alternative Solutions/Documentation': 5, 'Documentation Replicability': 6}
+label
+Documentation Replication on Other Examples    232
+Documentation Ambiguity                        211
+Requesting (Additional) Resources              162
+Lack of Alternative Solutions/Documentation    154
+Documentation Replicability                    139
+Documentation Completeness                     104
+Inadequate Examples                             83
+Name: count, dtype: int64
+label
+0    232
+3    211
+1    162
+5    154
+6    139
+4    104
+2     83
+Name: count, dtype: int64
+/opt/conda/lib/python3.10/site-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.
+  self.comm = Comm(**args)
+{'Documentation Replication on Other Examples': 0, 'Requesting (Additional) Resources': 1, 'Inadequate Examples': 2, 'Documentation Ambiguity': 3, 'Documentation Completeness': 4, 'Lack of Alternative Solutions/Documentation': 5, 'Documentation Replicability': 6}
+label
+Documentation Replication on Other Examples    232
+Documentation Ambiguity                        211
+Requesting (Additional) Resources              162
+Lack of Alternative Solutions/Documentation    154
+Documentation Replicability                    139
+Documentation Completeness                     104
+Inadequate Examples                             83
+Name: count, dtype: int64
+label
+0    232
+3    211
+1    162
+5    154
+6    139
+4    104
+2     83
+Name: count, dtype: int64
+/opt/conda/lib/python3.10/site-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.
+  self.comm = Comm(**args)
+Class Weights: tensor([0.7858, 0.8505, 0.9236, 0.8059, 0.9046, 0.8579, 0.8717],
+       device='cuda:0')
+Some weights of BertForSequenceClassification were not initialized from the model checkpoint at lanwuwei/BERTOverflow_stackoverflow_github and are newly initialized: ['classifier.bias', 'classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+Some weights of BertForSequenceClassification were not initialized from the model checkpoint at lanwuwei/BERTOverflow_stackoverflow_github and are newly initialized: ['classifier.bias', 'classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
+dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
+  warnings.warn(
+{'Documentation Replication on Other Examples': 0, 'Requesting (Additional) Resources': 1, 'Inadequate Examples': 2, 'Documentation Ambiguity': 3, 'Documentation Completeness': 4, 'Lack of Alternative Solutions/Documentation': 5, 'Documentation Replicability': 6}
+label
+Documentation Replication on Other Examples    232
+Documentation Ambiguity                        211
+Requesting (Additional) Resources              162
+Lack of Alternative Solutions/Documentation    154
+Documentation Replicability                    139
+Documentation Completeness                     104
+Inadequate Examples                             83
+Name: count, dtype: int64
+label
+0    232
+3    211
+1    162
+5    154
+6    139
+4    104
+2     83
+Name: count, dtype: int64
+/opt/conda/lib/python3.10/site-packages/ipywidgets/widgets/widget.py:503: DeprecationWarning: The `ipykernel.comm.Comm` class has been deprecated. Please use the `comm` module instead.For creating comms, use the function `from comm import create_comm`.
+  self.comm = Comm(**args)
+Class Weights: tensor([0.7858, 0.8505, 0.9236, 0.8059, 0.9046, 0.8579, 0.8717],
+       device='cuda:0')
+Some weights of BertForSequenceClassification were not initialized from the model checkpoint at lanwuwei/BERTOverflow_stackoverflow_github and are newly initialized: ['classifier.bias', 'classifier.weight']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
+dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.

wandb/run-20240410_155650-albqrbhg/files/requirements.txt

@@ -0,0 +1,863 @@
+Babel==2.14.0
+Boruta==0.3
+Brotli==1.0.9
+CVXcanon==0.1.2
+Cartopy==0.22.0
+Cython==3.0.8
+Deprecated==1.2.14
+Farama-Notifications==0.0.4
+Flask==3.0.2
+Geohash==1.0
+GitPython==3.1.41
+ImageHash==4.3.1
+Janome==0.5.0
+Jinja2==3.1.2
+LunarCalendar==0.0.9
+Mako==1.3.2
+Markdown==3.5.2
+MarkupSafe==2.1.3
+MarkupSafe==2.1.5
+Pillow==9.5.0
+PuLP==2.8.0
+PyArabic==0.6.15
+PyJWT==2.8.0
+PyMeeus==0.5.12
+PySocks==1.7.1
+PyUpSet==0.1.1.post7
+PyWavelets==1.5.0
+PyYAML==6.0.1
+Pygments==2.17.2
+Pympler==1.0.1
+QtPy==2.4.1
+Rtree==1.2.0
+SQLAlchemy==2.0.25
+SecretStorage==3.3.3
+Send2Trash==1.8.2
+Shapely==1.8.5.post1
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+Theano-PyMC==1.1.2
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+cachetools==4.2.4
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None}
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'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['BertModel'], 'finetuning_task': None, 'id2label': {0: 'Documentation Replication on Other Examples', 1: 'Requesting (Additional) Resources', 2: 'Inadequate Examples', 3: 'Documentation Ambiguity', 4: 'Documentation Completeness', 5: 'Lack of Alternative Solutions/Documentation', 6: 'Documentation Replicability'}, 'label2id': {'Documentation Replication on Other Examples': 0, 'Requesting (Additional) Resources': 1, 'Inadequate Examples': 2, 'Documentation Ambiguity': 3, 'Documentation Completeness': 4, 'Lack of Alternative Solutions/Documentation': 5, 'Documentation Replicability': 6}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': None, 'pad_token_id': 0, 'eos_token_id': None, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'lanwuwei/BERTOverflow_stackoverflow_github', 'transformers_version': '4.39.3', '_num_labels': 51, 'model_type': 'bert', 'output_past': True, 'vocab_size': 82000, 'hidden_size': 768, 'num_hidden_layers': 12, 'num_attention_heads': 12, 'hidden_act': 'gelu', 'intermediate_size': 3072, 'hidden_dropout_prob': 0.1, 'attention_probs_dropout_prob': 0.1, 'max_position_embeddings': 512, 'type_vocab_size': 2, 'initializer_range': 0.02, 'layer_norm_eps': 1e-12, 'position_embedding_type': 'absolute', 'use_cache': True, 'classifier_dropout': None, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 16, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 1e-05, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 5, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 0, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr10_16-14-35_ae604480b8c9', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None}
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'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['BertModel'], 'finetuning_task': None, 'id2label': {0: 'Documentation Replication on Other Examples', 1: 'Requesting (Additional) Resources', 2: 'Inadequate Examples', 3: 'Documentation Ambiguity', 4: 'Documentation Completeness', 5: 'Lack of Alternative Solutions/Documentation', 6: 'Documentation Replicability'}, 'label2id': {'Documentation Replication on Other Examples': 0, 'Requesting (Additional) Resources': 1, 'Inadequate Examples': 2, 'Documentation Ambiguity': 3, 'Documentation Completeness': 4, 'Lack of Alternative Solutions/Documentation': 5, 'Documentation Replicability': 6}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': None, 'pad_token_id': 0, 'eos_token_id': None, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'lanwuwei/BERTOverflow_stackoverflow_github', 'transformers_version': '4.39.3', '_num_labels': 51, 'model_type': 'bert', 'output_past': True, 'vocab_size': 82000, 'hidden_size': 768, 'num_hidden_layers': 12, 'num_attention_heads': 12, 'hidden_act': 'gelu', 'intermediate_size': 3072, 'hidden_dropout_prob': 0.1, 'attention_probs_dropout_prob': 0.1, 'max_position_embeddings': 512, 'type_vocab_size': 2, 'initializer_range': 0.02, 'layer_norm_eps': 1e-12, 'position_embedding_type': 'absolute', 'use_cache': True, 'classifier_dropout': None, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 16, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 1e-05, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 5, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 0, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr10_16-17-22_ae604480b8c9', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 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None}