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my_awesome_UkrSynth_model
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: 0.2091
- Precision: 0.9196
- Recall: 0.9203
- F1: 0.9200
- Accuracy: 0.9351
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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.786 | 1.0 | 500 | 0.3620 | 0.8661 | 0.8650 | 0.8655 | 0.8894 |
0.3278 | 2.0 | 1000 | 0.2486 | 0.9051 | 0.9041 | 0.9046 | 0.9223 |
0.2515 | 3.0 | 1500 | 0.2185 | 0.9155 | 0.9168 | 0.9162 | 0.9321 |
0.218 | 4.0 | 2000 | 0.2091 | 0.9196 | 0.9203 | 0.9200 | 0.9351 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3