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-clinc
results: []
distilbert-base-uncased-distilled-clinc
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: 0.2691
- Accuracy: 0.9461
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 |
|---|---|---|---|---|
| No log | 1.0 | 318 | 1.5992 | 0.7345 |
| 1.9427 | 2.0 | 636 | 0.8091 | 0.8684 |
| 1.9427 | 3.0 | 954 | 0.4730 | 0.9148 |
| 0.7363 | 4.0 | 1272 | 0.3512 | 0.9335 |
| 0.3518 | 5.0 | 1590 | 0.3056 | 0.9403 |
| 0.3518 | 6.0 | 1908 | 0.2886 | 0.9435 |
| 0.2547 | 7.0 | 2226 | 0.2780 | 0.9452 |
| 0.2245 | 8.0 | 2544 | 0.2729 | 0.9465 |
| 0.2245 | 9.0 | 2862 | 0.2696 | 0.9468 |
| 0.2137 | 10.0 | 3180 | 0.2691 | 0.9461 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1