distilbert-base-multilingual-cased_dna_ro_m12
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0541
- Accuracy: 0.982
- Accuracy Refusal: 0.997
- Precision: 0.976
- Precision Refusal: 0.975
- Recall: 0.98
- Recall Refusal: 0.99
- F1: 0.978
- F1 Refusal: 0.982
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: 50
- eval_batch_size: 100
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Accuracy Refusal | Precision | Precision Refusal | Recall | Recall Refusal | F1 | F1 Refusal |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.3288 | 1.0 | 1465 | 0.2399 | 0.917 | 0.989 | 0.888 | 0.941 | 0.9 | 0.916 | 0.893 | 0.928 |
| 0.1885 | 2.0 | 2930 | 0.1140 | 0.96 | 0.993 | 0.95 | 0.937 | 0.953 | 0.984 | 0.951 | 0.959 |
| 0.1253 | 3.0 | 4395 | 0.0541 | 0.982 | 0.997 | 0.976 | 0.975 | 0.98 | 0.99 | 0.978 | 0.982 |
Framework versions
- Transformers 4.43.1
- Pytorch 2.3.0+cu118
- Datasets 2.16.1
- Tokenizers 0.19.1
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