metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-fineturned-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: 0.94
distilbert-base-uncased-fineturned-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: 0.0266
- Accuracy: 0.94
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: 0.0004
- train_batch_size: 1024
- eval_batch_size: 1024
- 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 |
|---|---|---|---|---|
| 1.0233 | 1.0 | 15 | 0.4949 | 0.5413 |
| 0.2713 | 2.0 | 30 | 0.1338 | 0.8471 |
| 0.1284 | 3.0 | 45 | 0.0607 | 0.9165 |
| 0.0591 | 4.0 | 60 | 0.0407 | 0.9310 |
| 0.0487 | 5.0 | 75 | 0.0346 | 0.9358 |
| 0.0397 | 6.0 | 90 | 0.0308 | 0.9377 |
| 0.0372 | 7.0 | 105 | 0.0287 | 0.9390 |
| 0.0345 | 8.0 | 120 | 0.0275 | 0.9406 |
| 0.0333 | 9.0 | 135 | 0.0267 | 0.9394 |
| 0.0324 | 10.0 | 150 | 0.0266 | 0.94 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3