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: 0.9419354838709677
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: 0.1662
- Accuracy: 0.9419
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 |
---|---|---|---|---|
1.4626 | 1.0 | 318 | 0.9384 | 0.7232 |
0.7233 | 2.0 | 636 | 0.4417 | 0.8648 |
0.375 | 3.0 | 954 | 0.2598 | 0.9181 |
0.2407 | 4.0 | 1272 | 0.2047 | 0.9323 |
0.1932 | 5.0 | 1590 | 0.1859 | 0.9394 |
0.1732 | 6.0 | 1908 | 0.1769 | 0.9377 |
0.162 | 7.0 | 2226 | 0.1718 | 0.9410 |
0.156 | 8.0 | 2544 | 0.1684 | 0.9410 |
0.1523 | 9.0 | 2862 | 0.1669 | 0.9416 |
0.1502 | 10.0 | 3180 | 0.1662 | 0.9419 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0
- Datasets 2.4.0
- Tokenizers 0.10.3