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google_flan-t5-base_ds100_upsample3000

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  1. 20250501_205156.log +96 -0
  2. added_tokens.json +102 -0
  3. config.json +61 -0
  4. generation_config.json +7 -0
  5. model.safetensors +3 -0
  6. special_tokens_map.json +125 -0
  7. spiece.model +3 -0
  8. tokenizer_config.json +942 -0
  9. training_args.bin +3 -0
20250501_205156.log ADDED
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1
+ [2025-05-01 20:51:56] Created output directory: train_results/google_flan-t5-base_ds100_upsample3000
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+ [2025-05-01 20:51:56] Chat mode disabled
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+ [2025-05-01 20:51:56] Model size is 3B or smaller (0 B). Using full fine-tuning.
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+ [2025-05-01 20:51:56] Adjusted parameters for t5 model:
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+ [2025-05-01 20:51:56] - LEARNING_RATE: 3e-4
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+ [2025-05-01 20:51:56] - BATCH_SIZE: 128
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+ [2025-05-01 20:51:56] - GRADIENT_ACCUMULATION_STEPS: 1
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+ [2025-05-01 20:51:56] No QA format data will be used
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+ [2025-05-01 20:51:56] Limiting dataset size to: 100 samples
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+ [2025-05-01 20:51:56] =======================================
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+ [2025-05-01 20:51:56] Starting training for model: google/flan-t5-base
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+ [2025-05-01 20:51:56] =======================================
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+ [2025-05-01 20:51:56] CUDA_VISIBLE_DEVICES: 0,1
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+ [2025-05-01 20:51:56] WANDB_PROJECT: wikidyk-ar
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+ [2025-05-01 20:51:56] DATA_PATH: data/wikidyk2022-2025_01082025_gpt-4o_evalv2_pages_formatted_combined_v2.json
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+ [2025-05-01 20:51:56] Global Batch Size: 256
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+ [2025-05-01 20:51:56] Data Size: 100
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+ [2025-05-01 20:51:56] Executing command: torchrun --nproc_per_node "2" --master-port 29501 src/train.py --model_name_or_path "google/flan-t5-base" --data_path "data/wikidyk2022-2025_01082025_gpt-4o_evalv2_pages_formatted_combined_v2.json" --output_dir "train_results/google_flan-t5-base_ds100_upsample3000" --num_upsample "3000" --per_device_train_batch_size "128" --gradient_accumulation_steps "1" --learning_rate "3e-4" --num_train_epochs "1" --model_max_length "32768" --report_to wandb --logging_steps 50 --save_strategy no --bf16 True --use_flash_attention_2 True --qa_data_ratio "-1" --predict_mask "false" --ds_size 100
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+ [2025-05-01 20:51:56] Training started at Thu May 1 08:51:56 PM UTC 2025
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+ W0501 20:51:57.453000 4129993 site-packages/torch/distributed/run.py:792]
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+ W0501 20:51:57.453000 4129993 site-packages/torch/distributed/run.py:792] *****************************************
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+ W0501 20:51:57.453000 4129993 site-packages/torch/distributed/run.py:792] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
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+ W0501 20:51:57.453000 4129993 site-packages/torch/distributed/run.py:792] *****************************************
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+ WARNING:root:Output directory: train_results/google_flan-t5-base_ds100_upsample3000
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+ WARNING:root:Output directory: train_results/google_flan-t5-base_ds100_upsample3000
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+ You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
27
+ You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
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+ WARNING:root:Loading data...
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+ WARNING:root:Loading data...
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+ WARNING:root:Dataset initialized with all QA data:
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+ WARNING:root: - 0 QA examples
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+ WARNING:root: - 100 fact examples with upsampling factor 3000
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+ WARNING:root: - Total examples: 300000
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+ WARNING:root:Dataset initialized with all QA data:
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+ WARNING:root: - 0 QA examples
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+ WARNING:root: - 100 fact examples with upsampling factor 3000
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+ WARNING:root: - Total examples: 300000
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+ /home/wentao/yuwei/WikiDYKEvalV2/src/train.py:115: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `Trainer.__init__`. Use `processing_class` instead.
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+ trainer = Trainer(model=model, tokenizer=tokenizer, args=training_args, **data_module)
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+ /home/wentao/yuwei/WikiDYKEvalV2/src/train.py:115: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `Trainer.__init__`. Use `processing_class` instead.
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+ trainer = Trainer(model=model, tokenizer=tokenizer, args=training_args, **data_module)
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+ wandb: WARNING The `run_name` is currently set to the same value as `TrainingArguments.output_dir`. If this was not intended, please specify a different run name by setting the `TrainingArguments.run_name` parameter.
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+ /home/wentao/miniconda3/envs/wikidyk/lib/python3.10/site-packages/transformers/tokenization_utils_base.py:3980: UserWarning: `as_target_tokenizer` is deprecated and will be removed in v5 of Transformers. You can tokenize your labels by using the argument `text_target` of the regular `__call__` method (either in the same call as your input texts if you use the same keyword arguments, or in a separate call.
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+ warnings.warn(
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+ Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.48.0. You should pass an instance of `EncoderDecoderCache` instead, e.g. `past_key_values=EncoderDecoderCache.from_legacy_cache(past_key_values)`.
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+ [rank1]:[W501 20:52:03.133093715 reducer.cpp:1400] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
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+ wandb: Currently logged in as: yuweiz to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
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+ wandb: Tracking run with wandb version 0.19.10
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+ wandb: Run data is saved locally in /home/wentao/yuwei/WikiDYKEvalV2/wandb/run-20250501_205203-oh62mic6
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+ wandb: Run `wandb offline` to turn off syncing.
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+ wandb: Syncing run train_results/google_flan-t5-base_ds100_upsample3000
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+ wandb: ⭐️ View project at https://wandb.ai/yuweiz/wikidyk-ar
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+ wandb: 🚀 View run at https://wandb.ai/yuweiz/wikidyk-ar/runs/oh62mic6
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+
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+ warnings.warn(
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+ Passing a tuple of `past_key_values` is deprecated and will be removed in Transformers v4.48.0. You should pass an instance of `EncoderDecoderCache` instead, e.g. `past_key_values=EncoderDecoderCache.from_legacy_cache(past_key_values)`.
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+ [rank0]:[W501 20:52:04.177949738 reducer.cpp:1400] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters in the forward pass. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters in the forward pass, consider turning this flag off. Note that this warning may be a false positive if your model has flow control causing later iterations to have unused parameters. (function operator())
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535
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739
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741
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742
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745
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746
 
747
+
748
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749
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768
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769
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783
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785
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786
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787
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788
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790
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794
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795
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796
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798
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799
 
800
+
801
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802
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804
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805
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808
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810
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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825
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827
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830
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832
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833
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834
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835
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840
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843
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846
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847
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850
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851
  64%|██████▍ | 750/1172 [02:50<01:36, 4.38it/s]
852
 
853
+
854
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855
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864
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865
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866
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867
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868
  65%|██████▌ | 764/1172 [02:53<01:32, 4.41it/s]
869
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870
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871
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872
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873
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875
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880
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881
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882
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883
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886
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887
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888
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889
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890
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891
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892
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893
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894
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895
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896
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897
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898
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899
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900
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901
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903
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904
  68%|██████▊ | 800/1172 [03:01<01:24, 4.39it/s]
905
 
906
+
907
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908
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912
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915
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916
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917
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920
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921
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922
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924
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925
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926
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927
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928
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929
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934
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941
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942
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943
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944
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945
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946
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947
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948
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949
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950
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951
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952
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953
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954
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955
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956
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957
  73%|███████▎ | 850/1172 [03:13<01:13, 4.36it/s]
958
 
959
+
960
  73%|███████▎ | 850/1172 [03:13<01:13, 4.36it/s]
961
  73%|███████▎ | 851/1172 [03:13<01:13, 4.39it/s]
962
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963
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964
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965
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966
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967
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968
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969
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970
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971
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972
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973
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974
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975
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976
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977
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978
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979
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980
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981
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982
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983
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984
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985
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986
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987
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988
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989
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990
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991
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992
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993
  75%|███████▌ | 883/1172 [03:20<01:04, 4.51it/s]
994
  75%|███████▌ | 884/1172 [03:20<01:04, 4.44it/s]
995
  76%|███████▌ | 885/1172 [03:21<01:04, 4.46it/s]
996
  76%|███████▌ | 886/1172 [03:21<01:04, 4.44it/s]
997
  76%|███████▌ | 887/1172 [03:21<01:04, 4.40it/s]
998
  76%|███████▌ | 888/1172 [03:21<01:04, 4.39it/s]
999
  76%|███████▌ | 889/1172 [03:21<01:04, 4.38it/s]
1000
  76%|███████▌ | 890/1172 [03:22<01:04, 4.38it/s]
1001
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1002
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1003
  76%|███████▌ | 893/1172 [03:22<01:03, 4.42it/s]
1004
  76%|███████▋ | 894/1172 [03:23<01:02, 4.42it/s]
1005
  76%|███████▋ | 895/1172 [03:23<01:02, 4.41it/s]
1006
  76%|███████▋ | 896/1172 [03:23<01:02, 4.40it/s]
1007
  77%|███████▋ | 897/1172 [03:23<01:02, 4.43it/s]
1008
  77%|███████▋ | 898/1172 [03:24<01:02, 4.40it/s]
1009
  77%|███████▋ | 899/1172 [03:24<01:02, 4.39it/s]
1010
  77%|███████▋ | 900/1172 [03:24<01:02, 4.36it/s]
1011
 
1012
+
1013
  77%|███████▋ | 900/1172 [03:24<01:02, 4.36it/s]
1014
  77%|███████▋ | 901/1172 [03:24<01:01, 4.39it/s]
1015
  77%|███████▋ | 902/1172 [03:24<01:00, 4.43it/s]
1016
  77%|███████▋ | 903/1172 [03:25<01:01, 4.39it/s]
1017
  77%|███████▋ | 904/1172 [03:25<01:00, 4.46it/s]
1018
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1019
  77%|███████▋ | 906/1172 [03:25<00:59, 4.43it/s]
1020
  77%|███████▋ | 907/1172 [03:26<01:00, 4.40it/s]
1021
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1022
  78%|███████▊ | 909/1172 [03:26<00:59, 4.42it/s]
1023
  78%|███████▊ | 910/1172 [03:26<00:59, 4.41it/s]
1024
  78%|███████▊ | 911/1172 [03:26<00:59, 4.40it/s]
1025
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1026
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1027
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1028
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1029
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1030
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1031
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1032
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1033
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1034
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1035
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1036
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1037
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1038
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1039
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1040
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1041
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1042
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1043
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1044
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1045
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1046
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1047
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1048
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1049
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1050
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1051
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1052
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1053
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1054
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1055
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1056
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1058
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1063
  81%|████████ | 950/1172 [03:35<00:49, 4.48it/s]
1064
 
1065
+
1066
  81%|████████ | 950/1172 [03:35<00:49, 4.48it/s]
1067
  81%|████████ | 951/1172 [03:36<00:49, 4.42it/s]
1068
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1069
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1070
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1071
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1072
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1073
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1074
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1075
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1076
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1077
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1078
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1079
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1080
  82%|████████▏ | 964/1172 [03:38<00:47, 4.39it/s]
1081
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1082
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1083
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1084
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1085
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1086
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1087
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1088
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1089
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1090
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1091
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1092
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1093
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1094
  83%|████████▎ | 978/1172 [03:42<00:44, 4.40it/s]
1095
  84%|████████▎ | 979/1172 [03:42<00:44, 4.37it/s]
1096
  84%|████████▎ | 980/1172 [03:42<00:44, 4.35it/s]
1097
  84%|████████▎ | 981/1172 [03:42<00:44, 4.32it/s]
1098
  84%|████████▍ | 982/1172 [03:43<00:43, 4.35it/s]
1099
  84%|████████▍ | 983/1172 [03:43<00:42, 4.41it/s]
1100
  84%|████████▍ | 984/1172 [03:43<00:43, 4.36it/s]
1101
  84%|████████▍ | 985/1172 [03:43<00:42, 4.37it/s]
1102
  84%|████████▍ | 986/1172 [03:44<00:42, 4.37it/s]
1103
  84%|████████▍ | 987/1172 [03:44<00:42, 4.39it/s]
1104
  84%|████████▍ | 988/1172 [03:44<00:41, 4.40it/s]
1105
  84%|████████▍ | 989/1172 [03:44<00:41, 4.41it/s]
1106
  84%|████████▍ | 990/1172 [03:44<00:41, 4.37it/s]
1107
  85%|████████▍ | 991/1172 [03:45<00:41, 4.35it/s]
1108
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1109
  85%|████████▍ | 993/1172 [03:45<00:40, 4.43it/s]
1110
  85%|████████▍ | 994/1172 [03:45<00:40, 4.43it/s]
1111
  85%|████████▍ | 995/1172 [03:46<00:40, 4.39it/s]
1112
  85%|████████▍ | 996/1172 [03:46<00:39, 4.43it/s]
1113
  85%|████████▌ | 997/1172 [03:46<00:39, 4.38it/s]
1114
  85%|████████▌ | 998/1172 [03:46<00:40, 4.33it/s]
1115
  85%|████████▌ | 999/1172 [03:46<00:39, 4.38it/s]
1116
  85%|████████▌ | 1000/1172 [03:47<00:38, 4.43it/s]
1117
 
1118
+
1119
  85%|████████▌ | 1000/1172 [03:47<00:38, 4.43it/s]
1120
  85%|████████▌ | 1001/1172 [03:47<00:38, 4.46it/s]
1121
  85%|████████▌ | 1002/1172 [03:47<00:38, 4.44it/s]
1122
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1123
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1124
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1125
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1126
  86%|████████▌ | 1007/1172 [03:48<00:37, 4.38it/s]
1127
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1128
  86%|████████▌ | 1009/1172 [03:49<00:37, 4.38it/s]
1129
  86%|████████▌ | 1010/1172 [03:49<00:36, 4.43it/s]
1130
  86%|████████▋ | 1011/1172 [03:49<00:35, 4.50it/s]
1131
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1132
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1133
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1134
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1135
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1136
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1137
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1138
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1139
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1140
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1141
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1142
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1143
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1144
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1145
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1146
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1147
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1148
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1149
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1150
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1151
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1152
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+
1297
+ wandb:
1298
+ wandb: 🚀 View run train_results/google_flan-t5-base_ds100_upsample3000 at: https://wandb.ai/yuweiz/wikidyk-ar/runs/oh62mic6
1299
+ wandb: Find logs at: wandb/run-20250501_205203-oh62mic6/logs
1300
+ [rank0]:[W501 20:56:33.960710928 ProcessGroupNCCL.cpp:1496] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator())
1301
+ [2025-05-01 20:56:34] Training completed successfully for google/flan-t5-base
1302
+ [2025-05-01 20:56:34] Resource usage after training google/flan-t5-base:
1303
+ [2025-05-01 20:56:34] GPU memory usage:
1304
+ 1 MiB, 46068 MiB
1305
+ 1 MiB, 46068 MiB
1306
+ 535 MiB, 46068 MiB
1307
+ 4557 MiB, 46068 MiB
1308
+ [2025-05-01 20:56:34] Disk space usage for model outputs:
1309
+ 789M train_results/google_flan-t5-base_ds100_upsample3000
1310
+ [2025-05-01 20:56:34]
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