results

This model is a fine-tuned version of distilbert/distilroberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2147

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: 5e-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
• lr_scheduler_warmup_steps: 200
• num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss
0.1553	1.0	1521	0.1512
0.1561	2.0	3042	0.1484
0.1344	3.0	4563	0.1497
0.1119	4.0	6084	0.1551
0.1117	5.0	7605	0.1640
0.1095	6.0	9126	0.1729
0.0714	7.0	10647	0.1871
0.0617	8.0	12168	0.1950
0.048	9.0	13689	0.2021
0.0406	10.0	15210	0.2044
0.0264	11.0	16731	0.2077
0.0235	12.0	18252	0.2109
0.0218	13.0	19773	0.2116
0.0142	14.0	21294	0.2136
0.0131	15.0	22815	0.2143
0.0118	16.0	24336	0.2147

Framework versions

• Transformers 4.40.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1