xlm-roberta-large-xnli-finetuned-mnli-SJP-v2
This model is a fine-tuned version of joeddav/xlm-roberta-large-xnli on the swiss_judgment_prediction dataset. It achieves the following results on the evaluation set:
- Loss: 0.8093
- Accuracy: 0.5954
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 5 | 0.8879 | 0.5191 |
| No log | 2.0 | 10 | 0.8093 | 0.5954 |
| No log | 3.0 | 15 | 2.4452 | 0.3176 |
| No log | 4.0 | 20 | 3.6636 | 0.3084 |
| No log | 5.0 | 25 | 3.7687 | 0.3393 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Dataset used to train tuni/xlm-roberta-large-xnli-finetuned-mnli-SJP-v2
Evaluation results
- Accuracy on swiss_judgment_predictionself-reported0.595