| | --- |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: XLMRoberta-base-amazon-massive-Intent |
| | results: [] |
| | widget: |
| | - text: staubsauge den flur |
| | datasets: |
| | - AmazonScience/massive |
| | language: |
| | - en |
| | - ru |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # XLMRoberta-base-amazon-massive-Intent |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the MASSIVE dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5620 |
| | - Accuracy: 0.8751 |
| | - F1: 0.8269 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 7e-06 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
| | | 2.4641 | 1.0 | 1440 | 1.4258 | 0.6709 | 0.4126 | |
| | | 1.1447 | 2.0 | 2880 | 0.8477 | 0.8060 | 0.6318 | |
| | | 0.7437 | 3.0 | 4320 | 0.6688 | 0.8409 | 0.7060 | |
| | | 0.5543 | 4.0 | 5760 | 0.6006 | 0.8601 | 0.7813 | |
| | | 0.4375 | 5.0 | 7200 | 0.5780 | 0.8635 | 0.7937 | |
| | | 0.3763 | 6.0 | 8640 | 0.5748 | 0.8694 | 0.8170 | |
| | | 0.3265 | 7.0 | 10080 | 0.5620 | 0.8751 | 0.8269 | |
| | | 0.2916 | 8.0 | 11520 | 0.5701 | 0.8756 | 0.8260 | |
| | | 0.2628 | 9.0 | 12960 | 0.5728 | 0.8760 | 0.8271 | |
| | | 0.2474 | 10.0 | 14400 | 0.5740 | 0.8770 | 0.8288 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.0 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
