metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
model-index:
- name: banking-intent-distilbert-classifier
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: banking77
type: banking77
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.925
banking-intent-distilbert-classifier
This model is a fine-tuned version of distilbert-base-uncased on the banking77 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3307
- Accuracy: 0.925
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0124 | 1.0 | 313 | 0.3307 | 0.925 |
| 0.0102 | 2.0 | 626 | 0.3331 | 0.9289 |
| 0.0077 | 3.0 | 939 | 0.3381 | 0.9282 |
| 0.0062 | 4.0 | 1252 | 0.3406 | 0.9276 |
| 0.0059 | 5.0 | 1565 | 0.3423 | 0.9282 |
| 0.0045 | 6.0 | 1878 | 0.3445 | 0.9282 |
| 0.0046 | 7.0 | 2191 | 0.3458 | 0.9286 |
| 0.0041 | 8.0 | 2504 | 0.3470 | 0.9286 |
| 0.0038 | 9.0 | 2817 | 0.3472 | 0.9286 |
| 0.0034 | 10.0 | 3130 | 0.3475 | 0.9286 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0