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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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datasets: |
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- xtreme |
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metrics: |
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- f1 |
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model-index: |
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- name: xlm-roberta-base-finetuned-panx-de-1 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: xtreme |
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type: xtreme |
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config: PAN-X.de |
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split: validation |
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args: PAN-X.de |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8709714026327735 |
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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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# xlm-roberta-base-finetuned-panx-de-1 |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1707 |
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- F1: 0.8710 |
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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: 5e-05 |
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- train_batch_size: 96 |
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- eval_batch_size: 96 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 132 | 0.1593 | 0.8122 | |
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| No log | 2.0 | 264 | 0.1484 | 0.8427 | |
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| No log | 3.0 | 396 | 0.1399 | 0.8508 | |
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| 0.1703 | 4.0 | 528 | 0.1395 | 0.8560 | |
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| 0.1703 | 5.0 | 660 | 0.1409 | 0.8562 | |
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| 0.1703 | 6.0 | 792 | 0.1523 | 0.8648 | |
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| 0.1703 | 7.0 | 924 | 0.1554 | 0.8660 | |
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| 0.0448 | 8.0 | 1056 | 0.1633 | 0.8681 | |
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| 0.0448 | 9.0 | 1188 | 0.1664 | 0.8678 | |
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| 0.0448 | 10.0 | 1320 | 0.1707 | 0.8710 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
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