longformer_sciq

This model is a fine-tuned version of allenai/longformer-base-4096 on the sciq dataset. It achieves the following results on the evaluation set:

• Loss: 0.1479
• Accuracy: 0.932

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 25
• total_train_batch_size: 50
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	233	0.1650	0.934
No log	2.0	466	0.1479	0.932

Framework versions

• Transformers 4.21.3
• Pytorch 1.12.1
• Datasets 2.5.1
• Tokenizers 0.11.0