---
license: apache-2.0
base_model: Falconsai/text_summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: falcon-summ
  results: []
---

<!-- 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. -->

# falcon-summ

This model is a fine-tuned version of [Falconsai/text_summarization](https://huggingface.co/Falconsai/text_summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1784
- Rouge1: 0.1921
- Rouge2: 0.0958
- Rougel: 0.1642
- Rougelsum: 0.1643
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 62   | 2.6597          | 0.1336 | 0.0451 | 0.1109 | 0.1109    | 19.0    |
| No log        | 2.0   | 124  | 2.5126          | 0.1519 | 0.0584 | 0.1258 | 0.1259    | 19.0    |
| No log        | 3.0   | 186  | 2.4354          | 0.1702 | 0.0705 | 0.142  | 0.1422    | 19.0    |
| No log        | 4.0   | 248  | 2.3855          | 0.1915 | 0.0922 | 0.1616 | 0.1618    | 19.0    |
| No log        | 5.0   | 310  | 2.3499          | 0.1932 | 0.0939 | 0.1641 | 0.1644    | 19.0    |
| No log        | 6.0   | 372  | 2.3251          | 0.1951 | 0.0959 | 0.1665 | 0.1667    | 19.0    |
| No log        | 7.0   | 434  | 2.3035          | 0.1943 | 0.0963 | 0.1655 | 0.1656    | 19.0    |
| No log        | 8.0   | 496  | 2.2879          | 0.1941 | 0.0953 | 0.1652 | 0.1653    | 19.0    |
| 2.6368        | 9.0   | 558  | 2.2695          | 0.1952 | 0.0958 | 0.1665 | 0.1667    | 19.0    |
| 2.6368        | 10.0  | 620  | 2.2588          | 0.194  | 0.0952 | 0.1651 | 0.1653    | 19.0    |
| 2.6368        | 11.0  | 682  | 2.2476          | 0.1954 | 0.0968 | 0.1668 | 0.167     | 19.0    |
| 2.6368        | 12.0  | 744  | 2.2396          | 0.1944 | 0.0965 | 0.1656 | 0.1657    | 19.0    |
| 2.6368        | 13.0  | 806  | 2.2296          | 0.1929 | 0.0963 | 0.1641 | 0.1644    | 19.0    |
| 2.6368        | 14.0  | 868  | 2.2242          | 0.1928 | 0.0969 | 0.1639 | 0.1639    | 19.0    |
| 2.6368        | 15.0  | 930  | 2.2159          | 0.1935 | 0.0971 | 0.164  | 0.1641    | 19.0    |
| 2.6368        | 16.0  | 992  | 2.2114          | 0.1924 | 0.0965 | 0.164  | 0.1641    | 19.0    |
| 2.3506        | 17.0  | 1054 | 2.2077          | 0.1926 | 0.0973 | 0.1644 | 0.1645    | 19.0    |
| 2.3506        | 18.0  | 1116 | 2.2031          | 0.1933 | 0.0968 | 0.1647 | 0.1648    | 19.0    |
| 2.3506        | 19.0  | 1178 | 2.1971          | 0.1928 | 0.0962 | 0.1643 | 0.1644    | 19.0    |
| 2.3506        | 20.0  | 1240 | 2.1956          | 0.1925 | 0.0956 | 0.165  | 0.1651    | 19.0    |
| 2.3506        | 21.0  | 1302 | 2.1903          | 0.1927 | 0.0958 | 0.1644 | 0.1644    | 19.0    |
| 2.3506        | 22.0  | 1364 | 2.1882          | 0.1933 | 0.0972 | 0.1653 | 0.1653    | 19.0    |
| 2.3506        | 23.0  | 1426 | 2.1858          | 0.1921 | 0.0956 | 0.1639 | 0.1641    | 19.0    |
| 2.3506        | 24.0  | 1488 | 2.1842          | 0.1921 | 0.0956 | 0.1642 | 0.1643    | 19.0    |
| 2.2758        | 25.0  | 1550 | 2.1832          | 0.1919 | 0.0958 | 0.1645 | 0.1647    | 19.0    |
| 2.2758        | 26.0  | 1612 | 2.1815          | 0.1922 | 0.0958 | 0.1646 | 0.1647    | 19.0    |
| 2.2758        | 27.0  | 1674 | 2.1795          | 0.1924 | 0.0962 | 0.1646 | 0.1647    | 19.0    |
| 2.2758        | 28.0  | 1736 | 2.1790          | 0.1922 | 0.0961 | 0.1646 | 0.1647    | 19.0    |
| 2.2758        | 29.0  | 1798 | 2.1784          | 0.1925 | 0.0963 | 0.1645 | 0.1646    | 19.0    |
| 2.2758        | 30.0  | 1860 | 2.1784          | 0.1921 | 0.0958 | 0.1642 | 0.1643    | 19.0    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2