| --- |
| language: |
| - en |
| license: mit |
| tags: |
| - generated_from_trainer |
| - nlu |
| - intent-classification |
| datasets: |
| - AmazonScience/massive |
| metrics: |
| - accuracy |
| - f1 |
| pipeline_tag: text-classification |
| base_model: microsoft/mdeberta-v3-base |
| model-index: |
| - name: mdeberta-v3-base_amazon-massive_intent |
| results: |
| - task: |
| type: intent-classification |
| name: intent-classification |
| dataset: |
| name: MASSIVE |
| type: AmazonScience/massive |
| split: test |
| metrics: |
| - type: f1 |
| value: 0.8136 |
| 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. --> |
|
|
| # mdeberta-v3-base_amazon-massive_intent |
|
|
| This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the [MASSIVE1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1661 |
| - Accuracy: 0.8136 |
| - F1: 0.8136 |
|
|
| ## 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: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
| | 3.6412 | 1.0 | 720 | 2.7536 | 0.3123 | 0.3123 | |
| | 2.8575 | 2.0 | 1440 | 1.8556 | 0.5303 | 0.5303 | |
| | 1.7284 | 3.0 | 2160 | 1.3758 | 0.6699 | 0.6699 | |
| | 1.3794 | 4.0 | 2880 | 1.1221 | 0.7236 | 0.7236 | |
| | 0.942 | 5.0 | 3600 | 0.9936 | 0.7609 | 0.7609 | |
| | 0.7672 | 6.0 | 4320 | 0.9411 | 0.7727 | 0.7727 | |
| | 0.602 | 7.0 | 5040 | 0.9196 | 0.7841 | 0.7841 | |
| | 0.4776 | 8.0 | 5760 | 0.9328 | 0.7895 | 0.7895 | |
| | 0.4347 | 9.0 | 6480 | 0.9602 | 0.7860 | 0.7860 | |
| | 0.2941 | 10.0 | 7200 | 0.9543 | 0.7949 | 0.7949 | |
| | 0.2783 | 11.0 | 7920 | 0.9979 | 0.8013 | 0.8013 | |
| | 0.2038 | 12.0 | 8640 | 0.9702 | 0.8062 | 0.8062 | |
| | 0.1827 | 13.0 | 9360 | 1.0121 | 0.8106 | 0.8106 | |
| | 0.1352 | 14.0 | 10080 | 1.0339 | 0.8136 | 0.8136 | |
| | 0.1115 | 15.0 | 10800 | 1.1091 | 0.8057 | 0.8057 | |
| | 0.0996 | 16.0 | 11520 | 1.1134 | 0.8151 | 0.8151 | |
| | 0.0837 | 17.0 | 12240 | 1.1288 | 0.8160 | 0.8160 | |
| | 0.0711 | 18.0 | 12960 | 1.1499 | 0.8155 | 0.8155 | |
| | 0.0594 | 19.0 | 13680 | 1.1622 | 0.8126 | 0.8126 | |
| | 0.0569 | 20.0 | 14400 | 1.1661 | 0.8136 | 0.8136 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.24.0 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
