dsmsb/esg-class_bert_all_data_update_preprocess_0509

esg-classification_bert_all_data_0509

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1536
• Accuracy: 0.9643

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	69	1.4243	0.6245
No log	2.0	138	0.6974	0.7995
No log	3.0	207	0.3928	0.8965
No log	4.0	276	0.2440	0.9441
No log	5.0	345	0.1760	0.9606
No log	6.0	414	0.1536	0.9643

Framework versions

• Transformers 4.33.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3