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: 0.9435483870967742
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: 0.2540
- Accuracy: 0.9435
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.5782 | 1.0 | 318 | 1.9025 | 0.7574 |
| 1.4836 | 2.0 | 636 | 1.0083 | 0.8674 |
| 0.8085 | 3.0 | 954 | 0.5846 | 0.9187 |
| 0.4816 | 4.0 | 1272 | 0.4023 | 0.9339 |
| 0.3265 | 5.0 | 1590 | 0.3224 | 0.9429 |
| 0.2479 | 6.0 | 1908 | 0.2838 | 0.9426 |
| 0.2071 | 7.0 | 2226 | 0.2644 | 0.9445 |
| 0.186 | 8.0 | 2544 | 0.2564 | 0.9432 |
| 0.1771 | 9.0 | 2862 | 0.2540 | 0.9435 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0
- Datasets 2.0.0
- Tokenizers 0.10.3