Edit model card

bigbird_pegasus

This model is a fine-tuned version of google/bigbird-pegasus-large-arxiv on the None dataset. It achieves the following results on the evaluation set:

  • Loss: nan

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: 3e-05
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • lr_scheduler_warmup_steps: 500
  • training_steps: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.0 0.0 500 nan
0.0 0.01 1000 nan
0.0 0.01 1500 nan
0.0 0.01 2000 nan
0.0 0.02 2500 nan
0.0 0.02 3000 nan
0.0 0.02 3500 nan
0.0 0.03 4000 nan
0.0 0.03 4500 nan
0.0 0.03 5000 nan
0.0 0.04 5500 nan
0.0 0.04 6000 nan
0.0 0.05 6500 nan
0.0 0.05 7000 nan
0.0 0.05 7500 nan
0.0 0.06 8000 nan
0.0 0.06 8500 nan
0.0 0.06 9000 nan
0.0 0.07 9500 nan
0.0 0.07 10000 nan
0.0 0.07 10500 nan
0.0 0.08 11000 nan
0.0 0.08 11500 nan
0.0 0.08 12000 nan
0.0 0.09 12500 nan
0.0 0.09 13000 nan
0.0 0.09 13500 nan
0.0 0.1 14000 nan
0.0 0.1 14500 nan
0.0 0.1 15000 nan
0.0 0.11 15500 nan
0.0 0.11 16000 nan
0.0 0.11 16500 nan
0.0 0.12 17000 nan
0.0 0.12 17500 nan
0.0 0.13 18000 nan
0.0 0.13 18500 nan
0.0 0.13 19000 nan
0.0 0.14 19500 nan
0.0 0.14 20000 nan

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.1
Downloads last month
5
Safetensors
Model size
577M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for alshelt/bigbird_pegasus

Finetuned
(2)
this model