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: 0.9496774193548387
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: 0.2819
- Accuracy: 0.9497
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 |
|---|---|---|---|---|
| 2.8206 | 1.0 | 318 | 2.0803 | 0.7535 |
| 1.6059 | 2.0 | 636 | 1.0697 | 0.8665 |
| 0.8427 | 3.0 | 954 | 0.6011 | 0.9206 |
| 0.4898 | 4.0 | 1272 | 0.4185 | 0.9361 |
| 0.3321 | 5.0 | 1590 | 0.3450 | 0.9435 |
| 0.26 | 6.0 | 1908 | 0.3129 | 0.9477 |
| 0.2225 | 7.0 | 2226 | 0.2949 | 0.9494 |
| 0.2021 | 8.0 | 2544 | 0.2876 | 0.9481 |
| 0.1913 | 9.0 | 2862 | 0.2843 | 0.9494 |
| 0.1871 | 10.0 | 3180 | 0.2819 | 0.9497 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.12.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3