| --- |
| 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 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.22.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
