classify-ISIN-STEP7_binary

This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0002
• Accuracy: 1.0
• F1: 1.0
• Precision: 1.0
• Recall: 1.0
• Accuracy Label gd622:null: 0.0
• Accuracy Label Gd622:null: 1.0
• Accuracy Label Gd622:yes: 1.0

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Accuracy Label gd622:null	Accuracy Label Gd622:null	Accuracy Label Gd622:yes
0.2172	2.0833	100	0.1748	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0224	4.1667	200	0.0035	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0015	6.25	300	0.0014	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0098	8.3333	400	0.0007	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0094	10.4167	500	0.0004	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0003	12.5	600	0.0003	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0002	14.5833	700	0.0002	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0002	16.6667	800	0.0002	1.0	1.0	1.0	1.0	0.0	1.0	1.0
0.0002	18.75	900	0.0002	1.0	1.0	1.0	1.0	0.0	1.0	1.0

Framework versions

• Transformers 4.43.3
• Pytorch 2.4.0
• Datasets 2.20.0
• Tokenizers 0.19.1