DerivedFunction/distilbert-finance-sec

distilbert-dapt

This model is a fine-tuned version of distilbert/distilbert-base-uncased on a dataset. It achieves the following results on the evaluation set:

• Loss: 1.3623

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: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.8489	0.1195	500	1.7333
1.6703	0.2390	1000	1.5837
1.5914	0.3585	1500	1.5023
1.5805	0.4780	2000	1.4578
1.5379	0.5975	2500	1.4236
1.4827	0.7170	3000	1.4011
1.4549	0.8365	3500	1.3739
1.4450	0.9560	4000	1.3623

Framework versions

• Transformers 5.2.0
• Pytorch 2.10.0+cu128
• Datasets 4.3.0
• Tokenizers 0.22.2