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unable to reconize any word but the loss is decreasing??? #46

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ethio-artifical opened this issue Jan 26, 2024 · 1 comment
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@ethio-artifical
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ethio-artifical commented Jan 26, 2024

hello, i get an error on the training phase The loss is decreasing but when i evaluate the model it doesn't recognize any word i get 100 always.
i install pytorch 1.13.0
python 3.10.13
ctcdecode-1.0.3

this is my log file

Sat Jan 27 01:36:04 2024 ] Parameters:

{'work_dir': 'PATH_TO_SAVE_RESULTS', 'config': './configs/baseline.yaml', 'random_fix': True, 'device': '0', 'phase': 'train', 'save_interval': 5, 'random_seed': 0, 'eval_interval': 1, 'print_log': True, 'log_interval': 50, 'evaluate_tool': 'python', 'feeder': 'dataset.dataloader_video.BaseFeeder', 'dataset': 'phoenix14', 'dataset_info': {'dataset_root': './dataset/phoenix2014/phoenix-2014-multisigner', 'dict_path': './preprocess/phoenix2014/gloss_dict.npy', 'evaluation_dir': './evaluation/slr_eval', 'evaluation_prefix': 'phoenix2014-groundtruth'}, 'num_worker': 10, 'feeder_args': {'mode': 'test', 'datatype': 'video', 'num_gloss': -1, 'drop_ratio': 1.0, 'prefix': './dataset/phoenix2014/phoenix-2014-multisigner', 'transform_mode': False}, 'model': 'slr_network.SLRModel', 'model_args': {'num_classes': 65, 'c2d_type': 'resnet18', 'conv_type': 2, 'use_bn': 1, 'share_classifier': False, 'weight_norm': False}, 'load_weights': None, 'load_checkpoints': None, 'decode_mode': 'beam', 'ignore_weights': [], 'batch_size': 8, 'test_batch_size': 8, 'loss_weights': {'SeqCTC': 1.0}, 'optimizer_args': {'optimizer': 'Adam', 'base_lr': 0.0001, 'step': [20, 35], 'learning_ratio': 1, 'weight_decay': 0.0001, 'start_epoch': 0, 'nesterov': False}, 'num_epoch': 20}

[ Sat Jan 27 01:36:31 2024 ] Epoch: 0, Batch(0/122) done. Loss: 110.28868103 lr:0.000100
[ Sat Jan 27 01:38:26 2024 ] Epoch: 0, Batch(50/122) done. Loss: 13.18387794 lr:0.000100
[ Sat Jan 27 01:40:25 2024 ] Epoch: 0, Batch(100/122) done. Loss: 12.18678570 lr:0.000100
[ Sat Jan 27 01:41:07 2024 ] Mean training loss: 18.2596124587.
[ Sat Jan 27 01:41:58 2024 ] Dev WER: 100.00%
[ Sat Jan 27 01:42:24 2024 ] Epoch: 1, Batch(0/122) done. Loss: 12.15300369 lr:0.000100
[ Sat Jan 27 01:44:21 2024 ] Epoch: 1, Batch(50/122) done. Loss: 11.67739010 lr:0.000100
[ Sat Jan 27 01:46:22 2024 ] Epoch: 1, Batch(100/122) done. Loss: 13.26895523 lr:0.000100
[ Sat Jan 27 01:47:08 2024 ] Mean training loss: 12.1612764968.
[ Sat Jan 27 01:47:58 2024 ] Dev WER: 100.00%
[ Sat Jan 27 01:48:27 2024 ] Epoch: 2, Batch(0/122) done. Loss: 12.09643936 lr:0.000100
[ Sat Jan 27 01:50:20 2024 ] Epoch: 2, Batch(50/122) done. Loss: 11.06025696 lr:0.000100
[ Sat Jan 27 01:52:13 2024 ] Epoch: 2, Batch(100/122) done. Loss: 9.84243107 lr:0.000100
[ Sat Jan 27 01:53:01 2024 ] Mean training loss: 10.5143460211.
[ Sat Jan 27 01:53:52 2024 ] Dev WER: 100.00%
[ Sat Jan 27 01:54:22 2024 ] Epoch: 3, Batch(0/122) done. Loss: 9.38849068 lr:0.000100
[ Sat Jan 27 01:56:19 2024 ] Epoch: 3, Batch(50/122) done. Loss: 9.07399940 lr:0.000100
[ Sat Jan 27 01:58:09 2024 ] Epoch: 3, Batch(100/122) done. Loss: 8.66645050 lr:0.000100
[ Sat Jan 27 01:58:55 2024 ] Mean training loss: 9.0431265127.
[ Sat Jan 27 01:59:45 2024 ] Dev WER: 100.00%
[ Sat Jan 27 02:00:12 2024 ] Epoch: 4, Batch(0/122) done. Loss: 8.63507748 lr:0.000100
[ Sat Jan 27 02:02:05 2024 ] Epoch: 4, Batch(50/122) done. Loss: 7.65232229 lr:0.000100
[ Sat Jan 27 02:04:04 2024 ] Epoch: 4, Batch(100/122) done. Loss: 7.27032137 lr:0.000100
[ Sat Jan 27 02:04:47 2024 ] Mean training loss: 7.6128989556.
[ Sat Jan 27 02:05:38 2024 ] Dev WER: 100.00%
[ Sat Jan 27 02:06:09 2024 ] Epoch: 5, Batch(0/122) done. Loss: 6.52053165 lr:0.000100
[ Sat Jan 27 02:07:59 2024 ] Epoch: 5, Batch(50/122) done. Loss: 4.85380507 lr:0.000100
[ Sat Jan 27 02:10:03 2024 ] Epoch: 5, Batch(100/122) done. Loss: 7.19156647 lr:0.000100
[ Sat Jan 27 02:10:44 2024 ] Mean training loss: 5.7774419706.
[ Sat Jan 27 02:11:35 2024 ] Dev WER: 100.00%
[ Sat Jan 27 02:12:00 2024 ] Epoch: 6, Batch(0/122) done. Loss: 3.87025928 lr:0.000100
[ Sat Jan 27 02:14:02 2024 ] Epoch: 6, Batch(50/122) done. Loss: 3.52518511 lr:0.000100
[ Sat Jan 27 02:16:07 2024 ] Epoch: 6, Batch(100/122) done. Loss: 3.84364915 lr:0.000100
[ Sat Jan 27 02:16:45 2024 ] Mean training loss: 3.9095683430.
[ Sat Jan 27 02:17:36 2024 ] Dev WER: 100.00%
[ Sat Jan 27 02:18:05 2024 ] Epoch: 7, Batch(0/122) done. Loss: 3.43237042 lr:0.000100
[ Sat Jan 27 02:20:00 2024 ] Epoch: 7, Batch(50/122) done. Loss: 2.54930735 lr:0.000100
[ Sat Jan 27 02:21:59 2024 ] Epoch: 7, Batch(100/122) done. Loss: 2.43364787 lr:0.000100
[ Sat Jan 27 02:22:40 2024 ] Mean training loss: 2.6058940282.
[ Sat Jan 27 02:23:30 2024 ] Dev WER: 100.00%

WHAT IS THE PROBLEM GUYS and HOW TO SOLVE IT I AM TRYING IN ETHIOPIA SIGN LANGUAGE DATASET THAT IS AMHARIC CHARACTER

@ycmin95
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ycmin95 commented Feb 25, 2024

Perhaps you can check whether the sentence is decoded successfully and the groudtruth file is configured as wished.

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