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xlm-roberta-base-banking77-classification

Text Classification
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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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+ datasets:
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+ - banking77
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: xlm-roberta-base-banking77-classification
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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: banking77
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+ type: banking77
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9321428571428572
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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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+ # xlm-roberta-base-banking77-classification
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the banking77 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3034
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+ - Accuracy: 0.9321
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+ - F1 Score: 0.9321
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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: 64
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+ - eval_batch_size: 64
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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: 20
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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 Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 3.8002 | 1.0 | 157 | 2.7771 | 0.5159 | 0.4483 |
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+ | 2.4006 | 2.0 | 314 | 1.6937 | 0.7140 | 0.6720 |
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+ | 1.4633 | 3.0 | 471 | 1.0385 | 0.8308 | 0.8153 |
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+ | 0.9234 | 4.0 | 628 | 0.7008 | 0.8789 | 0.8761 |
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+ | 0.6163 | 5.0 | 785 | 0.5029 | 0.9068 | 0.9063 |
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+ | 0.4282 | 6.0 | 942 | 0.4084 | 0.9123 | 0.9125 |
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+ | 0.3203 | 7.0 | 1099 | 0.3515 | 0.9253 | 0.9253 |
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+ | 0.245 | 8.0 | 1256 | 0.3295 | 0.9227 | 0.9225 |
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+ | 0.1863 | 9.0 | 1413 | 0.3092 | 0.9269 | 0.9269 |
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+ | 0.1518 | 10.0 | 1570 | 0.2901 | 0.9338 | 0.9338 |
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+ | 0.1179 | 11.0 | 1727 | 0.2938 | 0.9318 | 0.9319 |
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+ | 0.0969 | 12.0 | 1884 | 0.2906 | 0.9328 | 0.9328 |
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+ | 0.0805 | 13.0 | 2041 | 0.2963 | 0.9295 | 0.9295 |
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+ | 0.063 | 14.0 | 2198 | 0.2998 | 0.9289 | 0.9288 |
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+ | 0.0554 | 15.0 | 2355 | 0.2933 | 0.9351 | 0.9349 |
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+ | 0.046 | 16.0 | 2512 | 0.2960 | 0.9328 | 0.9326 |
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+ | 0.04 | 17.0 | 2669 | 0.3032 | 0.9318 | 0.9318 |
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+ | 0.035 | 18.0 | 2826 | 0.3061 | 0.9312 | 0.9312 |
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+ | 0.0317 | 19.0 | 2983 | 0.3030 | 0.9331 | 0.9330 |
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+ | 0.0315 | 20.0 | 3140 | 0.3034 | 0.9321 | 0.9321 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.1
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1