Comments (3)
Have got
bleu1 bleu2 bleu3 bleu4 meteor
67.0 49.0 35.0 24.9 22.8
on MSCOCO dataset. However, it doesn't seem to attend to the right place though the sentence is pretty good. I follow the instruction of @Lorne0 and modify the attention type to stochastic one. To be clear, the visualization is almost the same at all time steps. In other words, the attention weights doesn't seem to learn to attend to the specific place at timestep t. Do anyone have some ideas about it?
My setup is
{'lrate': 0.01, 'decay_c': 0.0, 'patience': 10, 'save_per_epoch': True, 'n_layers_init': 2, 'RL_sumCost': True, 'max_epochs': 5000, 'dispFreq': 1, 'attn_type': 'stochastic', 'alpha_c': 1.0, 'temperature': 1.0, 'n_layers_att': 2, 'saveto': 'coco_stochastic_model.exp1.npl', 'ctx_dim': 512, 'valid_batch_size': 64, 'lstm_encoder': False, 'n_layers_lstm': 1, 'optimizer': 'adam', 'validFreq': 2000, 'dictionary': None, 'batch_size': 64, 'selector': True, 'n_words': 10500, 'dataset': 'coco', 'use_dropout_lstm': False, 'prev2out': True, 'dim': 1800, 'use_dropout': True, 'dim_word': 512, 'sampleFreq': 250, 'semi_sampling_p': 0.5, 'n_layers_out': 1, 'saveFreq': 1000, 'maxlen': 100, 'alpha_entropy_c': 0.002, 'ctx2out': True, 'reload_': False}
I've run 21 epochs.
Or alpha_visualization doesn't support a stochastic one? The paper only mentioned the visualization of the soft attention.
from arctic-captions.
I have the same problem too.
from arctic-captions.
@vyouman and @AMDS123 can you guys tell me how to start the code and train the dataset.
from arctic-captions.
Related Issues (20)
- Instructions to re-train the model: where to start?
- argument 'model' in the 'main function' (generate_caps.py)
- Split problem
- cannot figure out the code
- How soon does the sanity check look like working fine?
- where is model_name.npz? HOT 2
- Bug in doubly stochastic attention?
- A bug in setting Adam optimizer learning rate? HOT 2
- Trained Models HOT 2
- Questions or bugs in the adam optimizer HOT 1
- why don't finetune cnn? HOT 1
- question about "doubly stochastic attention" HOT 2
- How to get start and How the convolution works out HOT 3
- Can I get pkl files?
- f_init = theano.function([ctx], [ctx]+init_state+init_memory, name='f_init', profile=False)
- Where can I get "model_name.npz" to run the Jupyter Notebook example? HOT 1
- Dataset Format and Flow of Code
- Tensoflow implementation of this model?
- Step by step readme file
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