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run1.txt
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run1.txt
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~; python src/meta_bilstm/bin/train_model.py
{'meta_model_params': {'input_size': 512, 'hidden_dim': 512, 'num_layers': 1, 'dropout': 0.0}, 'word_model_params': {'hidden_dim': 256, 'mlp_proj_size': 256, 'num_layers': 1, 'dropout': 0.0, 'pretrained_embs_path': 'data/embeddings/model.txt'}, 'char_model_params': {'emb_dim': 100, 'hidden_dim': 256, 'mlp_proj_size': 256, 'num_layers': 1, 'dropout': 0.0}}
100%|██████████████████████████████████████████████| 248978/248978 [00:21<00:00, 11638.70it/s]
0it [00:00, ?it/s]Epochs 0, train step 0, train metrics:
{'acc': {'char': [0.022847101092338562],
'meta': [0.036906853318214417],
'word': [0.005272407550364733]},
'loss': {'char': [0.9329788684844971],
'meta': [2.8942558765411377],
'word': [2.909672737121582]}}
31it [02:51, 6.04s/it]
60it [06:02, 6.64s/it]Epochs 0, train step 60, train metrics:
{'acc': {'char': [0.5033222436904907],
'meta': [0.28737542033195496],
'word': [0.5614618062973022]},
'loss': {'char': [0.8349313735961914],
'meta': [1.8411591053009033],
'word': [1.398081660270691]}}
120it [12:07, 6.02s/it]Epochs 0, train step 120, train metrics:
{'acc': {'char': [0.5460829734802246],
'meta': [0.44009217619895935],
'word': [0.6267281174659729]},
'loss': {'char': [0.24652720987796783],
'meta': [1.7482649087905884],
'word': [1.2808362245559692]}}
180it [18:06, 5.09s/it]Epochs 0, train step 180, train metrics:
{'acc': {'char': [0.6076458692550659],
'meta': [0.5030180811882019],
'word': [0.6036217212677002]},
'loss': {'char': [0.19791266322135925],
'meta': [1.638064980506897],
'word': [1.1115890741348267]}}
240it [23:54, 5.90s/it]Epochs 0, train step 240, train metrics:
{'acc': {'char': [0.6335541009902954],
'meta': [0.5253863334655762],
'word': [0.6931567192077637]},
'loss': {'char': [0.22221381962299347],
'meta': [1.9326536655426025],
'word': [0.7616928219795227]}}
300it [29:14, 4.99s/it]Epochs 0, train step 300, train metrics:
{'acc': {'char': [0.6768707633018494],
'meta': [0.569727897644043],
'word': [0.7108843326568604]},
'loss': {'char': [0.16315799951553345],
'meta': [1.4514436721801758],
'word': [0.7756767272949219]}}
360it [34:48, 5.98s/it]Epochs 0, train step 360, train metrics:
{'acc': {'char': [0.7833935022354126],
'meta': [0.5469313859939575],
'word': [0.7364621162414551]},
'loss': {'char': [0.13296610116958618],
'meta': [1.4333710670471191],
'word': [0.745799720287323]}}
420it [41:05, 6.20s/it]Epochs 0, train step 420, train metrics:
{'acc': {'char': [0.77582848072052],
'meta': [0.44834306836128235],
'word': [0.7699804902076721]},
'loss': {'char': [0.12639285624027252],
'meta': [2.8917675018310547],
'word': [0.6519303321838379]}}
480it [46:48, 6.28s/it]Epochs 0, train step 480, train metrics:
{'acc': {'char': [0.8235294222831726],
'meta': [0.5126050710678101],
'word': [0.7848739624023438]},
'loss': {'char': [0.0953126773238182],
'meta': [3.961665391921997],
'word': [0.5831559300422668]}}
540it [52:45, 7.53s/it]Epochs 0, train step 540, train metrics:
{'acc': {'char': [0.8297162055969238],
'meta': [0.4323873221874237],
'word': [0.7996661067008972]},
'loss': {'char': [0.09747693687677383],
'meta': [3.311053514480591],
'word': [0.6903839707374573]}}
600it [58:32, 7.11s/it]Epochs 0, train step 600, train metrics:
{'acc': {'char': [0.8015414476394653],
'meta': [0.4238921105861664],
'word': [0.8034682273864746]},
'loss': {'char': [0.10077513754367828],
'meta': [5.534769535064697],
'word': [0.5213704705238342]}}
618it [1:00:24, 5.87s/it]^C
Traceback (most recent call last):
File "/mnt/Data/Documents/3-2/NNFL/group-ass/MetaBiLSTM/src/meta_bilstm/bin/train_model.py", line 43, in <module>
main()
File "/mnt/Data/Documents/3-2/NNFL/group-ass/MetaBiLSTM/src/meta_bilstm/bin/train_model.py", line 39, in main
trainer.train_model(5)
File "/home/prashant/.local/lib/python3.9/site-packages/meta_bilstm/train_utils/trainer.py", line 76, in train_model
batch_metrics = self.train_step(batch, optimizers)
File "/home/prashant/.local/lib/python3.9/site-packages/meta_bilstm/train_utils/trainer.py", line 129, in train_step
metrics['loss'][model_name].backward()
File "/home/prashant/.local/lib/python3.9/site-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/prashant/.local/lib/python3.9/site-packages/torch/autograd/__init__.py", line 130, in backward
Variable._execution_engine.run_backward(
KeyboardInterrupt