Eubinecto's workspace
Runs
117
Name
117 visualized
State
Notes
User
Tags
Created
Runtime
Sweep
batch_size
bos
depth
desc
entity
eos
fast_dev_run
hidden_size
limit_train_batches
limit_val_batches
log_every_n_steps
lr
max_epochs
max_length
model
module
num_classes
num_workers
pad
seed
shuffle
unk
upload
val_ratio
ver
vocab_size
Test/accuracy
Test/f1_score
Train/accuracy
Train/f1_score
Train/loss
Validation/accuracy
Validation/f1_score
Validation/loss
epoch
trainer/global_step
Failed
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eubinecto
11s
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1024
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2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = left
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false
512
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1
0.001
3
150
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rnn_for_classification
2
8
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1
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cls-nsmc-with-val-overfit-1
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Failed
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eubinecto
10s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = left
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-
false
512
-
-
1
0.001
3
150
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rnn_for_classification
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
4m 34s
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1024
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2
A baseline sentiment classifier (hence the `cls` prefix). It is trained on nsmc:with-val. Padding strategy = left. The number of weights is reduced to match RNN
eubinecto
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false
387
-
-
-
0.001
3
150
bilstm_for_classification
-
2
8
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1
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-
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cls-nsmc-with-val-reduced
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0.85394
0.85394
-
-
-
-
-
-
0
0
Finished
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eubinecto
2m 49s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is trained on nsmc:with-val. Padding strategy = left. The number of weights is reduced to match RNN
eubinecto
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false
443
-
-
-
0.001
3
150
lstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-reduced
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0.85188
0.85188
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-
-
-
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0
0
Finished
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eubinecto
36m 21s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is trained on nsmc:with-val. Padding strategy = left. The number of weights is reduced to match RNN
eubinecto
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false
387
-
-
1
0.001
3
150
bilstm_for_classification
-
2
2
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1
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cls-nsmc-with-val-reduced
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-
0.91474
0.91474
0.28958
0.8536
0.8536
0.34865
3
353
Finished
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eubinecto
20m 29s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is trained on nsmc:with-val. Padding strategy = left. The number of weights is reduced to match RNN
eubinecto
-
false
443
-
-
1
0.001
3
150
lstm_for_classification
-
2
2
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1
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cls-nsmc-with-val-reduced
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-
0.91707
0.91707
0.21912
0.85607
0.85607
0.35261
3
353
Finished
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eubinecto
15s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
443
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-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
18s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
445
-
-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
15s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
447
-
-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
15s
-
1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
450
-
-
1
0.001
3
150
lstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
17s
-
1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
387
-
-
1
0.001
3
150
bilstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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-
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Finished
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eubinecto
17s
-
1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
385
-
-
1
0.001
3
150
bilstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
18s
-
1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = left
eubinecto
-
true
512
-
-
1
0.001
3
150
rnn_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
26s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
390
-
-
1
0.001
3
150
bilstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
14s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
420
-
-
1
0.001
3
150
bilstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
20s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
440
-
-
1
0.001
3
150
bilstm_for_classification
-
2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
19s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
450
-
-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
22s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
460
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-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
19s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
470
-
-
1
0.001
3
150
lstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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Finished
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eubinecto
23s
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1024
-
2
A baseline sentiment classifier (hence the `cls` prefix). It is over-fitted to nsmc:with-val. Padding strategy = right
eubinecto
-
true
430
-
-
1
0.001
3
150
bilstm_for_classification
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2
8
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1
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cls-nsmc-with-val-overfit-1
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1-20
of 117