| | --- |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - xtreme |
| | metrics: |
| | - f1 |
| | model-index: |
| | - name: xlm-roberta-base-finetuned-panx-it |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: xtreme |
| | type: xtreme |
| | config: PAN-X.it |
| | split: validation |
| | args: PAN-X.it |
| | metrics: |
| | - name: F1 |
| | type: f1 |
| | value: 0.8253185367858611 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # xlm-roberta-base-finetuned-panx-it |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2588 |
| | - F1: 0.8253 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 24 |
| | - eval_batch_size: 24 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 0.8211 | 1.0 | 70 | 0.3441 | 0.7072 | |
| | | 0.2886 | 2.0 | 140 | 0.2724 | 0.7997 | |
| | | 0.1894 | 3.0 | 210 | 0.2588 | 0.8253 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
