prompt_fine_tuned_rte_XLMroberta

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.7052
• Accuracy: 0.3448
• F1: 0.3399

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6899	1.7241	50	0.7067	0.4138	0.3957
0.7066	3.4483	100	0.7054	0.4483	0.4221
0.6996	5.1724	150	0.7054	0.4483	0.4221
0.6876	6.8966	200	0.7056	0.4138	0.3957
0.699	8.6207	250	0.7051	0.4138	0.3957
0.6936	10.3448	300	0.7055	0.3448	0.3399
0.6909	12.0690	350	0.7052	0.3448	0.3399
0.69	13.7931	400	0.7052	0.3448	0.3399

Framework versions

• PEFT 0.11.1
• Transformers 4.41.0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1