metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results: []
distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1891
- Accuracy: 0.9448
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: 48
- eval_batch_size: 48
- 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 | 318 | 1.3062 | 0.7468 |
| 1.5816 | 2.0 | 636 | 0.6826 | 0.8810 |
| 1.5816 | 3.0 | 954 | 0.3967 | 0.9210 |
| 0.6178 | 4.0 | 1272 | 0.2761 | 0.9374 |
| 0.2869 | 5.0 | 1590 | 0.2292 | 0.9390 |
| 0.2869 | 6.0 | 1908 | 0.2099 | 0.9394 |
| 0.1934 | 7.0 | 2226 | 0.1993 | 0.9435 |
| 0.1622 | 8.0 | 2544 | 0.1937 | 0.9448 |
| 0.1622 | 9.0 | 2862 | 0.1904 | 0.9439 |
| 0.1503 | 10.0 | 3180 | 0.1891 | 0.9448 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1