deberta-v3-base_on5

This model is a fine-tuned version of microsoft/deberta-v3-base on the ontonotes5 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0776
• F1-type-match: 0.9325
• F1-partial: 0.9488
• F1-strict: 0.9046
• F1-exact: 0.9299

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1-type-match	F1-partial	F1-strict	F1-exact
0.0427	1.0	936	0.0674	0.9291	0.9452	0.8986	0.9246
0.0235	2.0	1873	0.0722	0.9281	0.9464	0.9002	0.9275
0.0148	3.0	2808	0.0776	0.9325	0.9488	0.9046	0.9299

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.15.0