bart-large-mnli_17082023T115544

This model is a fine-tuned version of facebook/bart-large-mnli on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4791
• Accuracy: 0.9394
• F1: 0.9528

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	142	0.2605	0.9095	0.9307
No log	2.0	284	0.2664	0.9183	0.9389
No log	2.99	426	0.2562	0.9315	0.9467
0.193	4.0	569	0.3992	0.9315	0.9458
0.193	5.0	711	0.4185	0.9315	0.9441
0.193	6.0	853	0.4918	0.9306	0.9462
0.193	6.99	995	0.4584	0.9385	0.9526
0.0101	8.0	1138	0.4611	0.9367	0.9503
0.0101	9.0	1280	0.4739	0.9385	0.9518
0.0101	9.98	1420	0.4791	0.9394	0.9528

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3