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: 1.3456
Accuracy: 0.7957

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	1.8460	0.7956
No log	2.0	10	1.3456	0.7957
No log	3.0	15	1.2799	0.7957
No log	4.0	20	1.2866	0.7957
No log	5.0	25	1.3162	0.7956

Framework versions

Transformers 4.20.0
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1

tuni/xlm-roberta-large-xnli-finetuned-mnli-SJP

xlm-roberta-large-xnli-finetuned-mnli-SJP

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tuni/
xlm-roberta-large-xnli-finetuned-mnli-SJP