metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc2
results: []
distilbert-base-uncased-distilled-clinc2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2271
- Accuracy: 0.9565
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: 0.0002134538968230803
- train_batch_size: 192
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1.7007007109718952e-07
- lr_scheduler_type: linear
- num_epochs: 13
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 80 | 0.4718 | 0.8939 |
| No log | 2.0 | 160 | 0.2975 | 0.9361 |
| No log | 3.0 | 240 | 0.2616 | 0.9494 |
| 0.5682 | 4.0 | 320 | 0.2531 | 0.9465 |
| 0.5682 | 5.0 | 400 | 0.2412 | 0.9523 |
| 0.5682 | 6.0 | 480 | 0.2452 | 0.9474 |
| 0.5682 | 7.0 | 560 | 0.2388 | 0.9503 |
| 0.1756 | 8.0 | 640 | 0.2342 | 0.9523 |
| 0.1756 | 9.0 | 720 | 0.2289 | 0.9542 |
| 0.1756 | 10.0 | 800 | 0.2290 | 0.9545 |
| 0.1756 | 11.0 | 880 | 0.2261 | 0.9558 |
| 0.1648 | 12.0 | 960 | 0.2267 | 0.9558 |
| 0.1648 | 13.0 | 1040 | 0.2271 | 0.9565 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1