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--- |
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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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- text-classification |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: multilingual_minilm-amazon_massive-intent_eu7 |
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results: |
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- task: |
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name: text-classification |
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type: text-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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- name: F1 |
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type: f1 |
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value: 0.8623 |
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datasets: |
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- AmazonScience/massive |
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language: |
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- en |
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- de |
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- fr |
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- it |
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- pt |
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- es |
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- pl |
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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_eu7 |
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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 [MASSIVE 1.1](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: 0.8238 |
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- Accuracy: 0.8623 |
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- F1: 0.8623 |
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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: 10 |
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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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| 1.3523 | 1.0 | 5038 | 1.3058 | 0.6937 | 0.6937 | |
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| 0.7842 | 2.0 | 10076 | 0.8434 | 0.8059 | 0.8059 | |
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| 0.5359 | 3.0 | 15114 | 0.7231 | 0.8302 | 0.8302 | |
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| 0.4106 | 4.0 | 20152 | 0.7121 | 0.8443 | 0.8443 | |
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| 0.3294 | 5.0 | 25190 | 0.7366 | 0.8497 | 0.8497 | |
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| 0.2621 | 6.0 | 30228 | 0.7702 | 0.8528 | 0.8528 | |
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| 0.2164 | 7.0 | 35266 | 0.7773 | 0.8577 | 0.8577 | |
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| 0.1756 | 8.0 | 40304 | 0.8080 | 0.8569 | 0.8569 | |
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| 0.1625 | 9.0 | 45342 | 0.8162 | 0.8624 | 0.8624 | |
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| 0.1448 | 10.0 | 50380 | 0.8238 | 0.8623 | 0.8623 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
