prompt_fine_tuned_CB_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: 1.4733
• Accuracy: 0.3182
• F1: 0.1536

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: 1
• eval_batch_size: 1
• 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
0.9542	0.4545	50	1.1060	0.3182	0.1536
0.8627	0.9091	100	1.1621	0.3182	0.1536
0.6647	1.3636	150	1.2304	0.3182	0.1536
0.8065	1.8182	200	1.3215	0.3182	0.1536
0.7675	2.2727	250	1.3718	0.3182	0.1536
0.8203	2.7273	300	1.4238	0.3182	0.1536
0.7817	3.1818	350	1.4576	0.3182	0.1536
0.7012	3.6364	400	1.4733	0.3182	0.1536

Framework versions

• PEFT 0.11.1
• Transformers 4.40.2
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1