---
license: apache-2.0
base_model: google/bigbird-pegasus-large-arxiv
tags:
- generated_from_trainer
model-index:
- name: bigbird_pegasus
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bigbird_pegasus

This model is a fine-tuned version of [google/bigbird-pegasus-large-arxiv](https://huggingface.co/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