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: 0.9387096774193548
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: 0.0985
- Accuracy: 0.9387
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 | 0.6287 | 0.7116 |
0.8898 | 2.0 | 636 | 0.2668 | 0.8510 |
0.8898 | 3.0 | 954 | 0.1559 | 0.9113 |
0.2678 | 4.0 | 1272 | 0.1246 | 0.9261 |
0.1446 | 5.0 | 1590 | 0.1124 | 0.9332 |
0.1446 | 6.0 | 1908 | 0.1059 | 0.9358 |
0.1178 | 7.0 | 2226 | 0.1025 | 0.9348 |
0.1071 | 8.0 | 2544 | 0.1007 | 0.9365 |
0.1071 | 9.0 | 2862 | 0.0988 | 0.9377 |
0.1021 | 10.0 | 3180 | 0.0985 | 0.9387 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.1+cu111
- Datasets 2.10.1
- Tokenizers 0.11.0