slurp-intent_baseline-distilbert-base-uncased
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6705
- Accuracy: 0.8701
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 2.7487 | 1.0 | 720 | 1.0701 | 0.7811 |
| 1.1513 | 2.0 | 1440 | 0.6923 | 0.8367 |
| 0.4843 | 3.0 | 2160 | 0.6241 | 0.8569 |
| 0.3823 | 4.0 | 2880 | 0.6058 | 0.8637 |
| 0.2328 | 5.0 | 3600 | 0.6172 | 0.8701 |
| 0.2081 | 6.0 | 4320 | 0.6486 | 0.8667 |
| 0.1472 | 7.0 | 5040 | 0.6541 | 0.8682 |
| 0.1345 | 8.0 | 5760 | 0.6552 | 0.8716 |
| 0.1215 | 9.0 | 6480 | 0.6695 | 0.8701 |
| 0.0999 | 10.0 | 7200 | 0.6705 | 0.8701 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 5
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.