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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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+ 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
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+ results: []
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+ ---
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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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+
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+ # multilingual_minilm-amazon-massive-intent
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+
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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 None 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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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