transformers pytorch longt5 text2text-generation generated_from_trainer dataset:learn3r/summ_screen_fd_bp model-index autotrain_compatible endpoints_compatible region:us
---
base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen_bp_only/checkpoint-210
datasets:
- learn3r/summ_screen_fd_bp
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: longt5_xl_summ_screen_bp_only_30
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: learn3r/summ_screen_fd_bp
      type: learn3r/summ_screen_fd_bp
    metrics:
    - type: rouge
      value: 40.4388
      name: Rouge1
---

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# longt5_xl_summ_screen_bp_only_30

This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen_bp_only/checkpoint-210](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_summ_screen_bp_only/checkpoint-210) on the learn3r/summ_screen_fd_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2376
- Rouge1: 40.4388
- Rouge2: 16.4662
- Rougel: 28.0771
- Rougelsum: 38.3405
- Gen Len: 246.7396

## 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: 0.0005
- 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: 15.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 0.324         | 0.97  | 14   | 2.2376          | 40.4388 | 16.4662 | 28.0771 | 38.3405   | 246.7396 |
| 0.2707        | 1.95  | 28   | 2.3204          | 40.2873 | 16.7641 | 27.3895 | 38.2689   | 307.3787 |
| 0.2217        | 2.99  | 43   | 2.5281          | 31.9916 | 13.8136 | 22.1895 | 30.623    | 501.9320 |
| 0.1776        | 3.97  | 57   | 2.7530          | 31.7535 | 13.8852 | 22.8653 | 30.3796   | 489.6183 |
| 0.1424        | 4.94  | 71   | 2.6578          | 32.117  | 14.2141 | 22.3733 | 30.8328   | 502.1124 |
| 0.1449        | 5.98  | 86   | 2.5508          | 35.3448 | 13.8478 | 24.9044 | 33.6108   | 357.3136 |
| 0.1191        | 6.96  | 100  | 3.1622          | 37.2189 | 16.0076 | 25.7011 | 35.294    | 408.8669 |
| 0.0879        | 8.0   | 115  | 2.8510          | 39.8825 | 16.8073 | 27.2428 | 37.9568   | 318.2278 |
| 0.0899        | 8.97  | 129  | 2.9138          | 31.7139 | 13.7066 | 21.8844 | 30.5075   | 500.4053 |
| 0.0656        | 9.95  | 143  | 3.1616          | 33.055  | 14.5841 | 22.5883 | 31.7565   | 488.1686 |
| 0.0542        | 10.99 | 158  | 3.3630          | 43.7514 | 18.9011 | 29.9017 | 41.6887   | 198.8077 |
| 0.0557        | 11.97 | 172  | 3.3826          | 42.3089 | 18.2735 | 29.0356 | 40.4154   | 270.9675 |
| 0.0542        | 12.94 | 186  | 3.4408          | 40.7691 | 16.529  | 28.3999 | 38.9723   | 186.7308 |
| 0.0596        | 13.98 | 201  | 3.5253          | 37.0037 | 15.9098 | 25.2808 | 35.3868   | 398.4704 |
| 0.0385        | 14.61 | 210  | 3.4990          | 32.5815 | 14.2951 | 22.4501 | 31.2928   | 499.3107 |


### Framework versions

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