The model can be trained using the following command:
python Video_seq2seq.py process_main --path_prj '/media/santanu/9eb9b6dc-b380-486e-b4fd-c424a325b976/Video Captioning/' --caption_file video_corpus.csv --feat_dir features --cnn_feat_dim 4096 --h_dim 512 --batch_size 32 --lstm_steps 80 --video_steps=80 --out_steps 20 --learning_rate 1e-4--epochs=100
|
Parameter |
Value |
| Optimizer | Adam |
| learning rate | 1e-4 |
| Batch size | 32 |
| Epochs |
100 |
| cnn_feat_dim |
4096 |
| lstm_steps |
80 |
| out_steps |
20 |
| h_dim |
512 |
The output log of the training is as follows:
Batch starting index: 1728 Epoch: 99 loss: 17.723186 Elapsed time: 0.21822428703308105
Batch starting index: 1760 Epoch: 99 loss: 19.556421 Elapsed time: 0.2106935977935791
Batch starting index: 1792 Epoch: 99 loss: 21.919321 Elapsed time: 0.2206578254699707
Batch starting index: 1824 Epoch: 99 loss...