---
base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_10/checkpoint-1360
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_bp
metrics:
- rouge
model-index:
- name: longt5_xl_gov_memsum_bp_15
  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: 35.319
---

<!-- 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_15

This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_10/checkpoint-1360](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_10/checkpoint-1360) on the learn3r/gov_report_memsum_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2731
- Rouge1: 35.319
- Rouge2: 11.8288
- Rougel: 16.3777
- Rougelsum: 33.5357
- Gen Len: 1942.3155

## 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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- 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   |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:---------:|
| 0.1366        | 1.0   | 272  | 3.2731          | 35.319  | 11.8288 | 16.3777 | 33.5357   | 1942.3155 |
| 0.1183        | 2.0   | 545  | 3.3957          | 37.5265 | 12.4932 | 16.743  | 35.7285   | 1867.3145 |
| 0.1072        | 3.0   | 818  | 3.4308          | 41.1487 | 13.4035 | 17.5783 | 39.1233   | 1561.0853 |
| 0.0909        | 4.0   | 1091 | 3.6078          | 41.2814 | 13.3137 | 17.9878 | 39.2664   | 1429.4604 |
| 0.0834        | 4.99  | 1360 | 3.8803          | 42.0328 | 13.9186 | 17.8203 | 39.9705   | 1559.3237 |


### Framework versions

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