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metadata
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: relevance-classification-v1
    results: []

relevance-classification-v1

This model is a fine-tuned version of allenai/longformer-base-4096 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 4.5156
  • Accuracy: 0.6069

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 338 0.6547 0.6138
0.744 2.0 676 1.3339 0.6069
0.8767 3.0 1014 0.6368 0.6207
0.8767 4.0 1352 0.8089 0.5931
0.82 5.0 1690 1.7406 0.6276
0.7448 6.0 2028 1.5868 0.6345
0.7448 7.0 2366 1.6950 0.6483
0.5449 8.0 2704 1.8365 0.6276
0.4678 9.0 3042 1.9301 0.6069
0.4678 10.0 3380 2.1818 0.6138
0.3283 11.0 3718 2.1599 0.6
0.2159 12.0 4056 2.3001 0.6207
0.2159 13.0 4394 2.3061 0.6138
0.1953 14.0 4732 2.5816 0.6069
0.1241 15.0 5070 2.7310 0.6069
0.1241 16.0 5408 2.5896 0.6207
0.1793 17.0 5746 2.7177 0.6207
0.0978 18.0 6084 2.6936 0.6069
0.0978 19.0 6422 2.4796 0.6069
0.175 20.0 6760 3.1355 0.6
0.1408 21.0 7098 3.0787 0.6069
0.1408 22.0 7436 3.0301 0.6
0.1127 23.0 7774 3.5055 0.5793
0.0812 24.0 8112 2.7603 0.6414
0.0812 25.0 8450 3.2282 0.5793
0.078 26.0 8788 3.3855 0.6138
0.0228 27.0 9126 3.2529 0.6
0.0228 28.0 9464 3.5188 0.6
0.0556 29.0 9802 3.3436 0.5931
0.0564 30.0 10140 3.6578 0.6069
0.0564 31.0 10478 3.6755 0.6069
0.0339 32.0 10816 3.5301 0.6138
0.0273 33.0 11154 3.8414 0.6069
0.0273 34.0 11492 4.0242 0.6069
0.0045 35.0 11830 4.2730 0.5931
0.0503 36.0 12168 3.8472 0.6069
0.0043 37.0 12506 4.1642 0.5931
0.0043 38.0 12844 4.2903 0.5931
0.0 39.0 13182 4.3893 0.5931
0.0 40.0 13520 4.4723 0.5931
0.0 41.0 13858 4.4564 0.5931
0.0088 42.0 14196 4.5376 0.5931
0.0375 43.0 14534 4.2578 0.6
0.0375 44.0 14872 4.3456 0.6069
0.0 45.0 15210 4.3547 0.6069
0.0002 46.0 15548 4.4010 0.6138
0.0002 47.0 15886 4.4475 0.6069
0.0 48.0 16224 4.4869 0.6069
0.0 49.0 16562 4.5066 0.6069
0.0 50.0 16900 4.5156 0.6069

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.16.0
  • Tokenizers 0.15.2