| --- |
| license: apache-2.0 |
| base_model: bert-base-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: intent-finetuned-intent-detection |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # intent-finetuned-intent-detection |
|
|
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/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 |
|
|
