metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
config: plus
split: validation
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9441935483870968
distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.1210
- Accuracy: 0.9442
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 | 0.7532 | 0.7613 |
0.9596 | 2.0 | 636 | 0.3779 | 0.8910 |
0.9596 | 3.0 | 954 | 0.2265 | 0.9239 |
0.3532 | 4.0 | 1272 | 0.1705 | 0.9345 |
0.1878 | 5.0 | 1590 | 0.1473 | 0.9390 |
0.1878 | 6.0 | 1908 | 0.1349 | 0.9419 |
0.1415 | 7.0 | 2226 | 0.1279 | 0.9452 |
0.1226 | 8.0 | 2544 | 0.1240 | 0.9448 |
0.1226 | 9.0 | 2862 | 0.1217 | 0.9435 |
0.1149 | 10.0 | 3180 | 0.1210 | 0.9442 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3