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longformer_quail

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

• eval_loss: 1.9568
• eval_accuracy: 0.5791
• eval_runtime: 44.254
• eval_samples_per_second: 12.564
• eval_steps_per_second: 6.282
• epoch: 4.0
• step: 816

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: 10

Framework versions

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