metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
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: 0.9419354838709677
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: 0.3313
- 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: 0.00016475242401724032
- 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: cosine
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 0.3697 | 0.9132 |
| 1.0928 | 2.0 | 636 | 0.3539 | 0.9226 |
| 1.0928 | 3.0 | 954 | 0.3790 | 0.9281 |
| 0.1164 | 4.0 | 1272 | 0.3579 | 0.9345 |
| 0.0587 | 5.0 | 1590 | 0.3705 | 0.9281 |
| 0.0587 | 6.0 | 1908 | 0.3543 | 0.9410 |
| 0.0344 | 7.0 | 2226 | 0.3665 | 0.9348 |
| 0.0244 | 8.0 | 2544 | 0.3510 | 0.9358 |
| 0.0244 | 9.0 | 2862 | 0.3344 | 0.9423 |
| 0.0153 | 10.0 | 3180 | 0.3335 | 0.9403 |
| 0.0153 | 11.0 | 3498 | 0.3302 | 0.9426 |
| 0.0126 | 12.0 | 3816 | 0.3305 | 0.9423 |
| 0.0103 | 13.0 | 4134 | 0.3301 | 0.9423 |
| 0.0103 | 14.0 | 4452 | 0.3311 | 0.9416 |
| 0.0095 | 15.0 | 4770 | 0.3313 | 0.9419 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.4.0
- Tokenizers 0.19.1