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: 0.0997
- Accuracy: 0.9416
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 | 0.5752 | 0.7177 |
| 0.7602 | 2.0 | 636 | 0.2803 | 0.8868 |
| 0.7602 | 3.0 | 954 | 0.1788 | 0.9216 |
| 0.2769 | 4.0 | 1272 | 0.1387 | 0.9355 |
| 0.1595 | 5.0 | 1590 | 0.1204 | 0.9358 |
| 0.1595 | 6.0 | 1908 | 0.1114 | 0.9368 |
| 0.1243 | 7.0 | 2226 | 0.1057 | 0.94 |
| 0.1097 | 8.0 | 2544 | 0.1022 | 0.9406 |
| 0.1097 | 9.0 | 2862 | 0.1002 | 0.9416 |
| 0.1035 | 10.0 | 3180 | 0.0997 | 0.9416 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1