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--- |
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language: |
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- en |
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license: mit |
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tags: |
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- generated_from_trainer |
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- nlu |
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- intent-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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pipeline_tag: text-classification |
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base_model: microsoft/Multilingual-MiniLM-L12-H384 |
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model-index: |
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- name: multilingual_minilm-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: 0.8234 |
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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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# multilingual_minilm-amazon-massive-intent |
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This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [MASSIVE1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8941 |
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- Accuracy: 0.8234 |
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- F1: 0.8234 |
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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: 15 |
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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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| 3.7961 | 1.0 | 720 | 3.1657 | 0.3404 | 0.3404 | |
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| 3.1859 | 2.0 | 1440 | 2.4835 | 0.4343 | 0.4343 | |
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| 2.3104 | 3.0 | 2160 | 2.0474 | 0.5652 | 0.5652 | |
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| 2.0071 | 4.0 | 2880 | 1.7190 | 0.6503 | 0.6503 | |
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| 1.5595 | 5.0 | 3600 | 1.4873 | 0.6990 | 0.6990 | |
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| 1.3664 | 6.0 | 4320 | 1.3088 | 0.7354 | 0.7354 | |
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| 1.1272 | 7.0 | 5040 | 1.1964 | 0.7521 | 0.7521 | |
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| 1.0128 | 8.0 | 5760 | 1.1115 | 0.7718 | 0.7718 | |
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| 0.9405 | 9.0 | 6480 | 1.0598 | 0.7841 | 0.7841 | |
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| 0.7758 | 10.0 | 7200 | 1.0003 | 0.7944 | 0.7944 | |
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| 0.7457 | 11.0 | 7920 | 0.9599 | 0.8037 | 0.8037 | |
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| 0.6605 | 12.0 | 8640 | 0.9175 | 0.8165 | 0.8165 | |
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| 0.6135 | 13.0 | 9360 | 0.9148 | 0.8190 | 0.8190 | |
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| 0.5698 | 14.0 | 10080 | 0.8976 | 0.8229 | 0.8229 | |
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| 0.5578 | 15.0 | 10800 | 0.8941 | 0.8234 | 0.8234 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
