xlm-roberta-test2
This model is a fine-tuned version of xlm-roberta-large-finetuned-conll03-german on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6979
- Precision: 0.8629
- Recall: 0.8761
- F1: 0.8694
- Accuracy: 0.8869
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 5
- label_smoothing_factor: 0.2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 125 | 3.0411 | 0.3632 | 0.4485 | 0.4014 | 0.4232 |
| No log | 2.0 | 250 | 2.1641 | 0.6046 | 0.6724 | 0.6367 | 0.6834 |
| No log | 3.0 | 375 | 1.9048 | 0.7506 | 0.7935 | 0.7715 | 0.7948 |
| 2.6262 | 4.0 | 500 | 1.7753 | 0.8306 | 0.8447 | 0.8376 | 0.8475 |
| 2.6262 | 5.0 | 625 | 1.6979 | 0.8629 | 0.8761 | 0.8694 | 0.8869 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.13.3
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