interpro_bert_2

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

• Loss: 0.4333

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: 0.0001
• train_batch_size: 256
• eval_batch_size: 128
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 2048
• total_eval_batch_size: 1024
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
1.2702	1.0	14395	1.1699
0.9079	2.0	28790	0.8665
0.7738	3.0	43185	0.7505
0.6959	4.0	57580	0.6820
0.6327	5.0	71975	0.6302
0.5899	6.0	86370	0.5956
0.5462	7.0	100765	0.5654
0.5155	8.0	115160	0.5395
0.4836	9.0	129555	0.5149
0.4633	10.0	143950	0.4984
0.441	11.0	158345	0.4774
0.4212	12.0	172740	0.4641
0.404	13.0	187135	0.4479
0.3883	14.0	201530	0.4401
0.3781	15.0	215925	0.4333

Framework versions

• Transformers 4.39.2
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2