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: 0.3323
- Accuracy: 0.9445
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.8211 | 1.0 | 318 | 2.0681 | 0.7261 |
1.6099 | 2.0 | 636 | 1.0738 | 0.8565 |
0.861 | 3.0 | 954 | 0.6203 | 0.9135 |
0.5164 | 4.0 | 1272 | 0.4480 | 0.9303 |
0.3683 | 5.0 | 1590 | 0.3843 | 0.9381 |
0.3024 | 6.0 | 1908 | 0.3578 | 0.9410 |
0.2706 | 7.0 | 2226 | 0.3411 | 0.9448 |
0.254 | 8.0 | 2544 | 0.3347 | 0.9452 |
0.2455 | 9.0 | 2862 | 0.3323 | 0.9445 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0