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distilt_bert_29_mva_intents
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: 0.2578
- Accuracy: 0.9561
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 | Accuracy |
---|---|---|---|---|
No log | 1.0 | 406 | 0.3952 | 0.9094 |
0.785 | 2.0 | 812 | 0.2136 | 0.9357 |
0.1929 | 3.0 | 1218 | 0.2459 | 0.9415 |
0.1016 | 4.0 | 1624 | 0.2041 | 0.9591 |
0.0631 | 5.0 | 2030 | 0.2268 | 0.9561 |
0.0631 | 6.0 | 2436 | 0.2304 | 0.9561 |
0.0391 | 7.0 | 2842 | 0.2425 | 0.9503 |
0.0246 | 8.0 | 3248 | 0.2594 | 0.9474 |
0.0239 | 9.0 | 3654 | 0.2522 | 0.9532 |
0.0171 | 10.0 | 4060 | 0.2578 | 0.9561 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1