distilbert-base-uncased-finetuned-nlp-letters-full-text-degendered-class-weighted
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0801
- F1: 0.7913
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
No log | 1.0 | 165 | 0.5891 | 0.2122 |
No log | 2.0 | 330 | 0.4626 | 0.2122 |
No log | 3.0 | 495 | 0.4237 | 0.6942 |
0.5036 | 4.0 | 660 | 0.5238 | 0.7538 |
0.5036 | 5.0 | 825 | 0.5471 | 0.7061 |
0.5036 | 6.0 | 990 | 0.6879 | 0.7355 |
0.2759 | 7.0 | 1155 | 0.8325 | 0.7850 |
0.2759 | 8.0 | 1320 | 0.9948 | 0.7743 |
0.2759 | 9.0 | 1485 | 1.0801 | 0.7913 |
0.1467 | 10.0 | 1650 | 1.1739 | 0.7897 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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