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: 0.2869
- Accuracy: 0.9410
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 | 3.1838 | 0.7265 |
| 3.7005 | 2.0 | 636 | 1.6176 | 0.8645 |
| 3.7005 | 3.0 | 954 | 0.8367 | 0.9087 |
| 1.3997 | 4.0 | 1272 | 0.5113 | 0.9303 |
| 0.4888 | 5.0 | 1590 | 0.3770 | 0.9355 |
| 0.4888 | 6.0 | 1908 | 0.3268 | 0.9374 |
| 0.2234 | 7.0 | 2226 | 0.2986 | 0.94 |
| 0.1355 | 8.0 | 2544 | 0.2889 | 0.9429 |
| 0.1355 | 9.0 | 2862 | 0.2869 | 0.9410 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1