| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| - nlu | |
| - text-classification | |
| datasets: | |
| - AmazonScience/massive | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: bert-base-uncased | |
| model-index: | |
| - name: bert-base-uncased-amazon-massive-intent | |
| results: | |
| - task: | |
| type: intent-classification | |
| name: intent-classification | |
| dataset: | |
| name: MASSIVE | |
| type: AmazonScience/massive | |
| split: test | |
| metrics: | |
| - type: f1 | |
| value: 0.8903 | |
| name: F1 | |
| <!-- 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. --> | |
| # bert-base-uncased-amazon-massive-intent | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on | |
| [Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset). | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.4897 | |
| - Accuracy: 0.8903 | |
| - F1: 0.8903 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 2.5862 | 1.0 | 720 | 1.0160 | 0.8096 | 0.8096 | | |
| | 1.0591 | 2.0 | 1440 | 0.6003 | 0.8716 | 0.8716 | | |
| | 0.4151 | 3.0 | 2160 | 0.5113 | 0.8859 | 0.8859 | | |
| | 0.3028 | 4.0 | 2880 | 0.5030 | 0.8883 | 0.8883 | | |
| | 0.1852 | 5.0 | 3600 | 0.4897 | 0.8903 | 0.8903 | | |
| ### Framework versions | |
| - Transformers 4.22.1 | |
| - Pytorch 1.12.1+cu113 | |
| - Datasets 2.5.1 | |
| - Tokenizers 0.12.1 |