---
base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280
tags:
- generated_from_trainer
datasets:
- learn3r/summ_screen_fd_bp
metrics:
- rouge
model-index:
- name: longt5_xl_sfd_bp_40
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: learn3r/summ_screen_fd_bp
      type: learn3r/summ_screen_fd_bp
    metrics:
    - name: Rouge1
      type: rouge
      value: 40.6965
---

<!-- 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_bp_40

This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280) on the learn3r/summ_screen_fd_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8277
- Rouge1: 40.6965
- Rouge2: 17.2793
- Rougel: 27.8429
- Rougelsum: 39.0726
- Gen Len: 294.0890

## 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: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 0.1033        | 0.97  | 14   | 3.1096          | 40.3355 | 16.0557 | 27.4642 | 38.6436   | 279.7507 |
| 0.0836        | 1.95  | 28   | 3.0361          | 38.2411 | 16.5448 | 26.6409 | 36.5841   | 368.4659 |
| 0.0717        | 2.99  | 43   | 2.9389          | 32.0114 | 13.7953 | 22.278  | 30.726    | 489.2047 |
| 0.0614        | 3.97  | 57   | 3.0221          | 32.969  | 13.7053 | 22.7428 | 31.6951   | 477.7240 |
| 0.1275        | 4.94  | 71   | 2.8277          | 40.6965 | 17.2793 | 27.8429 | 39.0726   | 294.0890 |
| 0.0511        | 5.98  | 86   | 3.0433          | 33.6479 | 15.0729 | 23.5443 | 32.3304   | 476.8457 |
| 0.0666        | 6.96  | 100  | 3.1150          | 37.743  | 16.2368 | 26.2524 | 36.1313   | 390.4362 |
| 0.0398        | 8.0   | 115  | 3.2225          | 41.3177 | 16.6663 | 28.7806 | 39.5914   | 203.4006 |
| 0.0396        | 8.97  | 129  | 3.1462          | 39.9605 | 16.6732 | 28.3459 | 38.226    | 123.8309 |
| 0.0466        | 9.95  | 143  | 3.2545          | 40.7977 | 16.9616 | 27.427  | 38.8973   | 298.5579 |
| 0.043         | 10.99 | 158  | 3.3188          | 36.6349 | 16.1781 | 25.1327 | 35.1793   | 425.1395 |
| 0.0538        | 11.97 | 172  | 2.8277          | 36.7878 | 15.1186 | 24.9774 | 35.275    | 394.8605 |
| 0.028         | 12.94 | 186  | 3.4398          | 42.9644 | 18.1812 | 29.1539 | 41.0465   | 188.1780 |
| 0.1056        | 13.98 | 201  | 3.3348          | 41.1626 | 17.1605 | 27.6558 | 39.2548   | 261.2967 |
| 0.0303        | 14.96 | 215  | 3.0238          | 42.2372 | 17.7292 | 28.8099 | 40.3325   | 231.6083 |
| 0.0234        | 16.0  | 230  | 3.3485          | 41.714  | 17.7161 | 27.9345 | 39.8519   | 306.1602 |
| 0.0263        | 16.97 | 244  | 3.2419          | 42.0014 | 17.2719 | 28.499  | 40.2024   | 210.7122 |
| 0.0225        | 17.95 | 258  | 3.3453          | 41.7766 | 17.7154 | 28.4692 | 39.9749   | 248.5786 |
| 0.0225        | 18.99 | 273  | 3.4441          | 42.1727 | 17.598  | 28.5122 | 40.4005   | 248.6380 |
| 0.0211        | 19.48 | 280  | 3.3211          | 42.5239 | 17.4102 | 28.6868 | 40.6537   | 200.3798 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1