sam_dfki

Bverma's group workspace

Group: unknown

1-1

of 1

Tags

Notes

Author

bverma

State

Finished

Start time

April 26th, 2022 1:36:30 PM

Runtime

5h 35m 54s

Tracked hours

5h 35m 48s

Run path

sam_dfki/best_rel_uncased/3pljg2y3

Linux-5.4.0-107-generic-x86_64-with-glibc2.10

Python version

3.8.10

Git repository

git clone git@github.com:ArneBinder/SAM.git

Git state

git checkout -b "splendid-microwave-1-4" b761d672e4cc2773e6cb2223c6e2e12bc8b43370

Command

/home/verma/Github/SAM/training_scripts/cross_validation/train-cross-validation.py train -f allennlp_configs/rel_best_uncased.jsonnet -s experiments/rel/best_rel_uncased/3pljg2y3 -o "{\"dataset_reader.num_shards\": 5, \"dataset_reader.dev_shard_idx\": 4, \"trainer.callbacks\": [{\"group\": \"unknown\", \"name\": \"splendid-microwave-1-4\", \"wandb_kwargs\": {\"job_type\": \"splendid-microwave-1\", \"id\": \"3pljg2y3\"}, \"type\": \"custom_wandb\", \"entity\": \"sam_dfki\", \"project\": \"best_rel_uncased\", \"files_to_save\": [\"config.json\", \"out.log\", \"metrics.json\"]}]}"

System Hardware

CPU count	96
GPU count	1
GPU type	NVIDIA RTX A6000

W&B CLI Version

0.12.0

Group

unknown

Job Type

splendid-microwave-1

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 6 keys
- ▶
  data_loader:{} 2 keys
  - batch_size:
    128
  - shuffle:
    true
- ▶
  dataset_reader:{} 16 keys
- ▶
  model:{} 7 keys
- train_data_path:
  "./dataset_scripts/sciarg.json@train"
- ▶
  trainer:{} 6 keys
- validation_data_path:
  "./dataset_scripts/sciarg.json@dev"

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 739 keys
- best_epoch:
  25
- best_validation__contradicts_rev/f1:
  0.6840149164199829
- best_validation__contradicts_rev/precision:
  0.8141592741012573
- best_validation__contradicts_rev/recall:
  0.5897436141967773
- best_validation__contradicts/f1:
  0.7138047218322754
- best_validation__contradicts/precision:
  0.7571428418159485
- best_validation__contradicts/recall:
  0.675159215927124
- best_validation__macro-f1/f1:
  0.8211629887421926
- best_validation__macro-f1/precision:
  0.863019863764445
- best_validation__macro-f1/recall:
  0.7872429390748342
- best_validation__micro-f1/precision:
  0.8839441537857056
- best_validation__micro-f1/recall:
  0.8068498373031616
- best_validation__NONE/f1:
  0.9689481854438782
- best_validation__NONE/precision:
  0.9552719593048096
- best_validation__NONE/recall:
  0.98302161693573
- best_validation__parts_of_same/f1:
  0.8120104670524597
- best_validation__parts_of_same/precision:
  0.8271276354789734
- best_validation__parts_of_same/recall:
  0.7974358797073364
- best_validation__supports_rev/f1:
  0.8742790818214417
- best_validation__supports_rev/precision:
  0.9132530093193054
- best_validation__supports_rev/recall:
  0.8384955525398254
- best_validation__supports/f1:
  0.8739205598831177
- best_validation__supports/precision:
  0.9111644625663756
- best_validation__supports/recall:
  0.8396017551422119
- best_validation_accuracy:
  0.939004975124378
- best_validation_loss:
  0.594786292767223
- best_validation_micro-f1/fscore:
  0.8436394333839417
- epoch:
  45
- gradient_mean/_classification_layer.bias:
  0.00000000258175236745
- gradient_mean/_classification_layer.weight:
  0.00000001944899885586
- gradient_mean/_seq2seq_encoder._module.bias_hh_l0:
  -0.00000055356736083922
- gradient_mean/_seq2seq_encoder._module.bias_hh_l0_reverse:
  0.00000146475031215232
- gradient_mean/_seq2seq_encoder._module.bias_hh_l1:
  -0.000000301662282709
- gradient_mean/_seq2seq_encoder._module.bias_hh_l1_reverse:
  -0.00000087779039859015
- gradient_mean/_seq2seq_encoder._module.bias_hh_l2:
  0.00000048248335815515
- gradient_mean/_seq2seq_encoder._module.bias_hh_l2_reverse:
  -0.00000050136105755882
- gradient_mean/_seq2seq_encoder._module.bias_hh_l3:
  0.00000036235118727745
- gradient_mean/_seq2seq_encoder._module.bias_hh_l3_reverse:
  -0.00000171034571394557
- gradient_mean/_seq2seq_encoder._module.bias_ih_l0:
  -0.00000055356736083922
- gradient_mean/_seq2seq_encoder._module.bias_ih_l0_reverse:
  0.00000146475031215232
- gradient_mean/_seq2seq_encoder._module.bias_ih_l1:
  -0.000000301662282709
- gradient_mean/_seq2seq_encoder._module.bias_ih_l1_reverse:
  -0.00000087779039859015
- gradient_mean/_seq2seq_encoder._module.bias_ih_l2:
  0.00000048248335815515
- gradient_mean/_seq2seq_encoder._module.bias_ih_l2_reverse:
  -0.00000050136105755882
- gradient_mean/_seq2seq_encoder._module.bias_ih_l3:
  0.00000036235118727745
- gradient_mean/_seq2seq_encoder._module.bias_ih_l3_reverse:
  -0.00000171034571394557
- validation/_supports/recall:
  0.8329645991325378
- validation/accuracy:
  0.934228855721393
- validation/loss:
  0.6543677548253084
- validation/micro-f1/fscore:
  0.8325849771499634

This run produced these artifacts as outputs. Total: 1. Learn more

wandb-history

run-3pljg2y3-history:v0