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framing_classification_longformer_30_augmented_multi

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metadata
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: framing_classification_longformer_30_augmented_multi
    results: []

framing_classification_longformer_30_augmented_multi

This model is a fine-tuned version of allenai/longformer-base-4096 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3585
  • Accuracy: 0.6170
  • F1: 0.1988
  • Precision: 0.2058
  • Recall: 0.2476

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Accuracy F1 Validation Loss Precision Recall
1.282 1.0 7043 0.5773 0.1691 1.5099 0.1473 0.2326
2.5135 2.0 14086 0.5455 0.1008 2.2716 0.0779 0.1429
2.384 3.0 21129 0.5455 0.1008 2.6195 0.0779 0.1429
2.5536 4.0 28172 0.5455 0.1008 2.3823 0.0779 0.1429
2.3549 5.0 35215 0.5455 0.1008 2.3964 0.0779 0.1429
2.3181 6.0 42258 0.5455 0.1008 2.4343 0.0779 0.1429
2.4398 7.0 49301 0.5455 0.1008 2.4609 0.0779 0.1429
2.3715 8.0 56344 0.5455 0.1008 2.4317 0.0779 0.1429
2.5554 9.0 63387 0.5455 0.1008 2.3966 0.0779 0.1429
1.3177 10.0 70430 0.5830 0.1707 1.4776 0.1472 0.2352
1.3928 11.0 77473 0.6159 0.1750 1.5114 0.1470 0.2348
1.5202 12.0 84516 0.6159 0.1746 1.4525 0.1465 0.2337
1.4013 13.0 91559 0.5909 0.1625 1.4524 0.1399 0.2113
1.4087 14.0 98602 0.5955 0.1736 1.4572 0.1484 0.2385
2.3755 15.0 105645 0.5727 0.1420 1.9328 0.1193 0.1771
2.2211 16.0 112688 0.5943 0.1596 1.7707 0.1317 0.2043
2.0359 17.0 119731 0.5830 0.1506 1.9399 0.1248 0.19
1.7553 18.0 126774 0.5920 0.1580 1.8171 0.1306 0.2026
1.4321 19.0 133817 0.6125 0.1733 1.4162 0.1462 0.2317
1.4545 20.0 140860 0.6068 0.1728 1.4446 0.1466 0.2324
1.3939 21.0 147903 0.6148 0.1747 1.4451 0.1473 0.2345
1.4333 22.0 154946 0.5841 0.1702 1.4462 0.1474 0.2333
1.3013 23.0 161989 0.6170 0.1757 1.4099 0.1480 0.2363
1.397 24.0 169032 0.6170 0.1766 1.4181 0.1489 0.2385
1.4752 25.0 176075 0.6136 0.1727 1.3997 0.1444 0.2297
1.372 26.0 183118 1.4134 0.6170 0.1748 0.1471 0.2340
1.4563 27.0 190161 1.3920 0.6205 0.1775 0.1492 0.2394
1.3727 28.0 197204 1.3763 0.6125 0.1737 0.1465 0.2328
1.4587 29.0 204247 1.3585 0.6170 0.1988 0.2058 0.2476
1.2723 30.0 211290 1.3586 0.6136 0.1973 0.1967 0.2455

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.14.4
  • Tokenizers 0.13.3