distilbert-base-uncased-finetuned-nlp-letters-s1_s2-none-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: 0.0007
- F1: 1.0
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 | 221 | 0.0007 | 1.0 |
| No log | 2.0 | 442 | 0.0003 | 1.0 |
| 0.0211 | 3.0 | 663 | 0.0001 | 1.0 |
| 0.0211 | 4.0 | 884 | 0.0001 | 1.0 |
| 0.0002 | 5.0 | 1105 | 0.0000 | 1.0 |
| 0.0002 | 6.0 | 1326 | 0.0000 | 1.0 |
| 0.0001 | 7.0 | 1547 | 0.0000 | 1.0 |
| 0.0001 | 8.0 | 1768 | 0.0000 | 1.0 |
| 0.0001 | 9.0 | 1989 | 0.0000 | 1.0 |
| 0.0 | 10.0 | 2210 | 0.0000 | 1.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for ben-yu/distilbert-base-uncased-finetuned-nlp-letters-s1_s2-none-class-weighted
Base model
distilbert/distilbert-base-uncased