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bert-base-uncased-eurlex
This model is a fine-tuned version of nlpaueb/bert-base-uncased-eurlex on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4164
- eval_Accuracy: 0.9224
- eval_F1_macro: 0.9301
- eval_F1_class_0: 0.8941
- eval_F1_class_1: 0.9388
- eval_F1_class_2: 0.9412
- eval_F1_class_3: 0.9730
- eval_F1_class_4: 0.9148
- eval_F1_class_5: 0.9573
- eval_F1_class_6: 0.9399
- eval_F1_class_7: 0.9685
- eval_F1_class_8: 0.9630
- eval_F1_class_9: 0.9495
- eval_F1_class_10: 0.8574
- eval_F1_class_11: 0.9241
- eval_F1_class_12: 0.8677
- eval_F1_class_13: 0.9442
- eval_F1_class_14: 0.9055
- eval_F1_class_15: 0.9022
- eval_F1_class_16: 0.8929
- eval_F1_class_17: 0.9811
- eval_F1_class_18: 0.8870
- eval_F1_class_19: 1.0
- eval_runtime: 154.2922
- eval_samples_per_second: 32.918
- eval_steps_per_second: 4.116
- epoch: 0.52
- step: 3000
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3