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--- |
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license: mit |
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base_model: xlm-roberta-base |
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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: XLMRoberta-base-amazon-massive-Intent |
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results: [] |
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widget: |
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- text: staubsauge den flur |
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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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- ru |
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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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# XLMRoberta-base-amazon-massive-Intent |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the MASSIVE dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5620 |
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- Accuracy: 0.8751 |
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- F1: 0.8269 |
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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: 7e-06 |
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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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| 2.4641 | 1.0 | 1440 | 1.4258 | 0.6709 | 0.4126 | |
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| 1.1447 | 2.0 | 2880 | 0.8477 | 0.8060 | 0.6318 | |
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| 0.7437 | 3.0 | 4320 | 0.6688 | 0.8409 | 0.7060 | |
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| 0.5543 | 4.0 | 5760 | 0.6006 | 0.8601 | 0.7813 | |
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| 0.4375 | 5.0 | 7200 | 0.5780 | 0.8635 | 0.7937 | |
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| 0.3763 | 6.0 | 8640 | 0.5748 | 0.8694 | 0.8170 | |
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| 0.3265 | 7.0 | 10080 | 0.5620 | 0.8751 | 0.8269 | |
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| 0.2916 | 8.0 | 11520 | 0.5701 | 0.8756 | 0.8260 | |
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| 0.2628 | 9.0 | 12960 | 0.5728 | 0.8760 | 0.8271 | |
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| 0.2474 | 10.0 | 14400 | 0.5740 | 0.8770 | 0.8288 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
