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
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9490322580645161
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: 0.3421
- Accuracy: 0.9490
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 |
---|---|---|---|---|
3.6932 | 1.0 | 318 | 2.7484 | 0.7497 |
2.1009 | 2.0 | 636 | 1.3756 | 0.8587 |
1.0477 | 3.0 | 954 | 0.7215 | 0.9174 |
0.5587 | 4.0 | 1272 | 0.4802 | 0.9352 |
0.3538 | 5.0 | 1590 | 0.3947 | 0.9445 |
0.2699 | 6.0 | 1908 | 0.3674 | 0.9435 |
0.2299 | 7.0 | 2226 | 0.3514 | 0.9474 |
0.2096 | 8.0 | 2544 | 0.3467 | 0.9487 |
0.1987 | 9.0 | 2862 | 0.3446 | 0.9477 |
0.1946 | 10.0 | 3180 | 0.3421 | 0.9490 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.1