metadata
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: 0.0365
- Accuracy: 0.9352
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 |
|---|---|---|---|---|
| 0.8234 | 1.0 | 318 | 0.4209 | 0.6758 |
| 0.3141 | 2.0 | 636 | 0.1440 | 0.8481 |
| 0.1458 | 3.0 | 954 | 0.0764 | 0.9065 |
| 0.0938 | 4.0 | 1272 | 0.0551 | 0.9190 |
| 0.0737 | 5.0 | 1590 | 0.0470 | 0.9277 |
| 0.0639 | 6.0 | 1908 | 0.0423 | 0.9303 |
| 0.0581 | 7.0 | 2226 | 0.0400 | 0.9352 |
| 0.0548 | 8.0 | 2544 | 0.0379 | 0.9358 |
| 0.0521 | 9.0 | 2862 | 0.0367 | 0.9358 |
| 0.0509 | 10.0 | 3180 | 0.0365 | 0.9352 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1