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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- nlu |
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- text-classification |
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datasets: |
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- AmazonScience/massive |
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metrics: |
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- accuracy |
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- f1 |
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base_model: bert-base-uncased |
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model-index: |
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- name: bert-base-uncased-amazon-massive-intent |
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results: |
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- task: |
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type: intent-classification |
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name: intent-classification |
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dataset: |
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name: MASSIVE |
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type: AmazonScience/massive |
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split: test |
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metrics: |
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- type: f1 |
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value: 0.8903 |
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name: F1 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-uncased-amazon-massive-intent |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on |
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[Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4897 |
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- Accuracy: 0.8903 |
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- F1: 0.8903 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 2.5862 | 1.0 | 720 | 1.0160 | 0.8096 | 0.8096 | |
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| 1.0591 | 2.0 | 1440 | 0.6003 | 0.8716 | 0.8716 | |
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| 0.4151 | 3.0 | 2160 | 0.5113 | 0.8859 | 0.8859 | |
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| 0.3028 | 4.0 | 2880 | 0.5030 | 0.8883 | 0.8883 | |
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| 0.1852 | 5.0 | 3600 | 0.4897 | 0.8903 | 0.8903 | |
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### Framework versions |
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- Transformers 4.22.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
