metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-finetuned-clinc
results: []
distilbert-base-uncased-distilled-finetuned-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: 0.2950
- Accuracy: 0.9439
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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.1681 | 0.7361 |
| 3.6771 | 2.0 | 636 | 1.6131 | 0.8616 |
| 3.6771 | 3.0 | 954 | 0.8311 | 0.9103 |
| 1.3903 | 4.0 | 1272 | 0.5136 | 0.93 |
| 0.4916 | 5.0 | 1590 | 0.3818 | 0.9365 |
| 0.4916 | 6.0 | 1908 | 0.3381 | 0.9365 |
| 0.2278 | 7.0 | 2226 | 0.3054 | 0.9410 |
| 0.1444 | 8.0 | 2544 | 0.2982 | 0.9435 |
| 0.1444 | 9.0 | 2862 | 0.2950 | 0.9439 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2