metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: intent-finetuned-intent-detection
results: []
intent-finetuned-intent-detection
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6938
- Accuracy: 0.8638
- F1: 0.8593
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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 3.0316 | 1.0 | 180 | 1.7788 | 0.6819 | 0.6352 |
| 1.4515 | 2.0 | 360 | 1.0539 | 0.7956 | 0.7735 |
| 0.9212 | 3.0 | 540 | 0.8143 | 0.8457 | 0.8382 |
| 0.6883 | 4.0 | 720 | 0.7246 | 0.8601 | 0.8544 |
| 0.583 | 5.0 | 900 | 0.6938 | 0.8638 | 0.8593 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2