Waynehills-NLP-doogie-AIHub-paper-summary

This model is a fine-tuned version of mimi/Waynehills-NLP-doogie on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 2.6206
• eval_runtime: 309.223
• eval_samples_per_second: 38.167
• eval_steps_per_second: 4.773
• epoch: 3.75
• step: 60000

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: 2
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Framework versions

• Transformers 4.12.2
• Pytorch 1.10.0+cu111
• Datasets 1.5.0
• Tokenizers 0.10.3