---
license: apache-2.0
base_model: Falconsai/text_summarization
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: text_summarization-finetuned
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 1.0.0
      split: validation
      args: 1.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2389
---

<!-- 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. -->

# text_summarization-finetuned

This model is a fine-tuned version of [Falconsai/text_summarization](https://huggingface.co/Falconsai/text_summarization) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8119
- Rouge1: 0.2389
- Rouge2: 0.1112
- Rougel: 0.1946
- Rougelsum: 0.2237

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 10.7536       | 1.0   | 78   | 6.6776          | 0.203  | 0.0868 | 0.1627 | 0.1909    |
| 5.0057        | 1.99  | 156  | 3.2391          | 0.2128 | 0.0909 | 0.1707 | 0.2003    |
| 3.3921        | 2.99  | 234  | 2.9233          | 0.2263 | 0.102  | 0.1849 | 0.213     |
| 3.1013        | 4.0   | 313  | 2.7724          | 0.2265 | 0.1043 | 0.1864 | 0.2128    |
| 2.9643        | 5.0   | 391  | 2.5935          | 0.2305 | 0.1075 | 0.1893 | 0.2166    |
| 2.7594        | 5.99  | 469  | 2.4411          | 0.2311 | 0.1075 | 0.1888 | 0.2171    |
| 2.6579        | 6.99  | 547  | 2.3273          | 0.2327 | 0.1084 | 0.1908 | 0.2185    |
| 2.5729        | 8.0   | 626  | 2.2452          | 0.2326 | 0.1083 | 0.1905 | 0.2185    |
| 2.4879        | 9.0   | 704  | 2.1828          | 0.2313 | 0.1063 | 0.1893 | 0.2176    |
| 2.401         | 9.99  | 782  | 2.1365          | 0.2336 | 0.1071 | 0.1907 | 0.2193    |
| 2.346         | 10.99 | 860  | 2.0937          | 0.2332 | 0.1065 | 0.1905 | 0.2192    |
| 2.3086        | 12.0  | 939  | 2.0606          | 0.2334 | 0.107  | 0.1905 | 0.2191    |
| 2.2648        | 13.0  | 1017 | 2.0315          | 0.2351 | 0.1085 | 0.1925 | 0.2211    |
| 2.2452        | 13.99 | 1095 | 2.0058          | 0.2354 | 0.1079 | 0.1922 | 0.221     |
| 2.204         | 14.99 | 1173 | 1.9853          | 0.2364 | 0.1093 | 0.1932 | 0.2222    |
| 2.1723        | 16.0  | 1252 | 1.9665          | 0.236  | 0.109  | 0.1931 | 0.2218    |
| 2.1601        | 17.0  | 1330 | 1.9479          | 0.2356 | 0.109  | 0.1923 | 0.2212    |
| 2.143         | 17.99 | 1408 | 1.9337          | 0.2356 | 0.1093 | 0.1926 | 0.2215    |
| 2.093         | 18.99 | 1486 | 1.9201          | 0.2366 | 0.1101 | 0.193  | 0.2223    |
| 2.0987        | 20.0  | 1565 | 1.9077          | 0.2371 | 0.111  | 0.1938 | 0.2228    |
| 2.0663        | 21.0  | 1643 | 1.8956          | 0.2368 | 0.1104 | 0.1937 | 0.2219    |
| 2.0629        | 21.99 | 1721 | 1.8858          | 0.2375 | 0.1109 | 0.1935 | 0.2221    |
| 2.0449        | 22.99 | 1799 | 1.8765          | 0.2395 | 0.1128 | 0.1959 | 0.2244    |
| 2.0342        | 24.0  | 1878 | 1.8684          | 0.2384 | 0.1115 | 0.1943 | 0.2233    |
| 2.0021        | 25.0  | 1956 | 1.8620          | 0.2373 | 0.1101 | 0.1932 | 0.222     |
| 2.0152        | 25.99 | 2034 | 1.8537          | 0.2387 | 0.1116 | 0.1949 | 0.2236    |
| 2.0058        | 26.99 | 2112 | 1.8477          | 0.239  | 0.1118 | 0.195  | 0.224     |
| 1.981         | 28.0  | 2191 | 1.8418          | 0.2377 | 0.1108 | 0.194  | 0.2227    |
| 1.9493        | 29.0  | 2269 | 1.8358          | 0.2388 | 0.111  | 0.1947 | 0.2234    |
| 1.9626        | 29.99 | 2347 | 1.8314          | 0.2385 | 0.1109 | 0.1945 | 0.223     |
| 1.9735        | 30.99 | 2425 | 1.8279          | 0.239  | 0.1109 | 0.1944 | 0.2232    |
| 1.9421        | 32.0  | 2504 | 1.8240          | 0.2393 | 0.1109 | 0.1946 | 0.2234    |
| 1.9371        | 33.0  | 2582 | 1.8212          | 0.2396 | 0.1114 | 0.1951 | 0.2239    |
| 1.9252        | 33.99 | 2660 | 1.8184          | 0.2392 | 0.1111 | 0.1947 | 0.2238    |
| 1.9556        | 34.99 | 2738 | 1.8163          | 0.2392 | 0.1111 | 0.1946 | 0.2238    |
| 1.9436        | 36.0  | 2817 | 1.8147          | 0.2394 | 0.111  | 0.1945 | 0.224     |
| 1.9444        | 37.0  | 2895 | 1.8132          | 0.239  | 0.1113 | 0.1946 | 0.2239    |
| 1.9368        | 37.99 | 2973 | 1.8125          | 0.239  | 0.1112 | 0.1947 | 0.2239    |
| 1.9467        | 38.99 | 3051 | 1.8120          | 0.2389 | 0.1112 | 0.1946 | 0.2237    |
| 1.9335        | 39.87 | 3120 | 1.8119          | 0.2389 | 0.1112 | 0.1946 | 0.2237    |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1