---
base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_bp
metrics:
- rouge
model-index:
- name: longt5_xl_gov_memsum_bp_20
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: learn3r/gov_report_memsum_bp
      type: learn3r/gov_report_memsum_bp
    metrics:
    - name: Rouge1
      type: rouge
      value: 42.5601
---

<!-- 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_gov_memsum_bp_20

This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360) on the learn3r/gov_report_memsum_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6259
- Rouge1: 42.5601
- Rouge2: 14.1791
- Rougel: 17.9691
- Rougelsum: 40.487
- Gen Len: 1510.8695

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len   |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:---------:|
| 0.1591        | 1.0   | 136  | 3.6259          | 42.5601 | 14.1791 | 17.9691 | 40.487    | 1510.8695 |
| 0.1186        | 1.99  | 272  | 3.7885          | 39.795  | 13.2493 | 17.3095 | 37.9065   | 1707.0401 |
| 0.097         | 3.0   | 409  | 4.0192          | 41.4441 | 13.4026 | 17.8804 | 39.4502   | 1442.7729 |
| 0.0818        | 4.0   | 545  | 4.1699          | 40.2374 | 13.5869 | 17.364  | 38.2969   | 1741.0236 |
| 0.0786        | 4.99  | 680  | 4.3339          | 39.5612 | 13.4283 | 17.3666 | 37.6526   | 1710.4111 |


### Framework versions

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