---
base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140
tags:
- generated_from_trainer
datasets:
- tau/scrolls
metrics:
- rouge
model-index:
- name: longt5_xl_summ_screen_20
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: tau/scrolls summ_screen_fd
      type: tau/scrolls
      config: summ_screen_fd
      split: validation
      args: summ_screen_fd
    metrics:
    - name: Rouge1
      type: rouge
      value: 28.1708
---

<!-- 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_summ_screen_20

This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140](https://huggingface.co.//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen/checkpoint-140) on the tau/scrolls summ_screen_fd dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1917
- Rouge1: 28.1708
- Rouge2: 6.6895
- Rougel: 18.1637
- Rougelsum: 24.3987
- Gen Len: 96.2041

## 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: 2
- 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 | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:|
| 0.4063        | 0.97  | 14   | 3.7385          | 27.9171 | 6.7215 | 17.9315 | 24.363    | 71.9083  |
| 0.3125        | 1.95  | 28   | 3.1917          | 28.1708 | 6.6895 | 18.1637 | 24.3987   | 96.2041  |
| 0.2177        | 2.99  | 43   | 3.9998          | 29.3167 | 5.9    | 17.3608 | 25.6945   | 198.0473 |
| 0.1753        | 3.97  | 57   | 4.2287          | 29.0605 | 6.2534 | 17.5744 | 25.6415   | 158.6509 |
| 0.2747        | 4.94  | 71   | 4.1027          | 31.2245 | 6.5663 | 18.1588 | 26.8996   | 118.4438 |
| 0.1045        | 5.98  | 86   | 5.0581          | 30.6056 | 6.8892 | 18.4933 | 26.4027   | 92.9882  |
| 0.0875        | 6.96  | 100  | 4.5941          | 32.5234 | 7.3736 | 18.8958 | 28.4738   | 160.8964 |
| 0.1572        | 8.0   | 115  | 4.9386          | 31.4658 | 7.2592 | 18.4796 | 27.6047   | 121.0178 |
| 0.0867        | 8.97  | 129  | 4.5565          | 32.0531 | 7.0692 | 18.5551 | 27.3373   | 160.4793 |
| 0.0748        | 9.74  | 140  | 5.0866          | 32.2717 | 7.7004 | 18.9107 | 28.3874   | 124.1893 |


### Framework versions

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