transformers pytorch longt5 text2text-generation generated_from_trainer dataset:learn3r/summ_screen_memsum_oracle model-index autotrain_compatible endpoints_compatible region:us
---
base_model: longt5_xl_summ_screen_memsum_20/checkpoint-140
datasets:
- learn3r/summ_screen_memsum_oracle
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: longt5_xl_summ_screen_25
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: learn3r/summ_screen_memsum_oracle
      type: learn3r/summ_screen_memsum_oracle
    metrics:
    - type: rouge
      value: 39.5624
      name: Rouge1
---

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# longt5_xl_summ_screen_25

This model is a fine-tuned version of [longt5_xl_summ_screen_memsum_20/checkpoint-140](https://huggingface.co/longt5_xl_summ_screen_memsum_20/checkpoint-140) on the learn3r/summ_screen_memsum_oracle dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0742
- Rouge1: 39.5624
- Rouge2: 10.2833
- Rougel: 21.2004
- Rougelsum: 34.0767
- Gen Len: 152.0325

## 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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 0.1846        | 0.97  | 14   | 4.6151          | 37.719  | 9.6532  | 20.2955 | 32.3806   | 100.9527 |
| 0.1441        | 1.95  | 28   | 4.1640          | 36.8632 | 9.6545  | 20.9349 | 31.8954   | 105.5799 |
| 0.1379        | 2.99  | 43   | 4.0742          | 39.5624 | 10.2833 | 21.2004 | 34.0767   | 152.0325 |
| 0.089         | 3.97  | 57   | 4.5216          | 40.2528 | 10.9254 | 21.6978 | 34.6793   | 176.0976 |
| 0.1028        | 4.87  | 70   | 4.1434          | 32.7739 | 9.1305  | 19.6246 | 27.9012   | 59.6775  |


### Framework versions

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