transformers pytorch longt5 text2text-generation generated_from_trainer dataset:tau/scrolls base_model:google/long-t5-tglobal-xl license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
- generated_from_trainer
datasets:
- tau/scrolls
model-index:
- name: longt5_xl_sfd_4096_e10
  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. -->

# longt5_xl_sfd_4096_e10

This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the tau/scrolls summ_screen_fd dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3255

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0332        | 0.97  | 14   | 2.5424          |
| 2.4105        | 1.95  | 28   | 2.3255          |
| 2.0496        | 2.99  | 43   | 2.3420          |
| 1.7473        | 3.97  | 57   | 2.3520          |
| 1.4007        | 4.94  | 71   | 2.4980          |
| 1.3809        | 5.98  | 86   | 2.4785          |
| 1.1153        | 6.96  | 100  | 2.7326          |
| 0.9129        | 8.0   | 115  | 2.9232          |
| 0.7118        | 8.97  | 129  | 3.0476          |
| 0.5883        | 9.74  | 140  | 3.3644          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
