transformers safetensors t5 text2text-generation summarization generated_from_trainer dataset:cnn_dailymail base_model:Falconsai/text_summarization base_model:finetune:Falconsai/text_summarization license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: Falconsai/text_summarization
datasets:
- cnn_dailymail
license: apache-2.0
metrics:
- rouge
pipeline_tag: summarization
tags:
- summarization
- generated_from_trainer
model-index:
- name: text_summarization-finetuned_cnn_dailymail
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 1.0.0
      split: validation
      args: 1.0.0
    metrics:
    - type: rouge
      value: 0.2361
      name: Rouge1
---

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# text_summarization-finetuned_cnn_dailymail

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: 2.0045
- Rouge1: 0.2361
- Rouge2: 0.11
- Rougel: 0.192
- Rougelsum: 0.2212

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 10.8721       | 0.99  | 62   | 8.1409          | 0.2058 | 0.0891 | 0.1673 | 0.1924    |
| 6.0137        | 2.0   | 125  | 4.2590          | 0.1997 | 0.082  | 0.1581 | 0.188     |
| 3.7261        | 2.99  | 187  | 3.0481          | 0.2196 | 0.0942 | 0.178  | 0.2066    |
| 3.3164        | 4.0   | 250  | 2.9085          | 0.2281 | 0.103  | 0.1852 | 0.2148    |
| 3.1784        | 4.99  | 312  | 2.7974          | 0.2282 | 0.1057 | 0.1869 | 0.2155    |
| 3.0345        | 6.0   | 375  | 2.6655          | 0.2318 | 0.1084 | 0.189  | 0.2177    |
| 2.8946        | 6.99  | 437  | 2.5411          | 0.2332 | 0.1095 | 0.1906 | 0.2193    |
| 2.7696        | 8.0   | 500  | 2.4400          | 0.2333 | 0.111  | 0.1916 | 0.22      |
| 2.684         | 8.99  | 562  | 2.3651          | 0.2342 | 0.11   | 0.1924 | 0.2204    |
| 2.6073        | 10.0  | 625  | 2.3010          | 0.2344 | 0.111  | 0.1922 | 0.2205    |
| 2.5517        | 10.99 | 687  | 2.2522          | 0.2346 | 0.1108 | 0.1925 | 0.2207    |
| 2.4845        | 12.0  | 750  | 2.2108          | 0.2327 | 0.1098 | 0.1916 | 0.2186    |
| 2.4484        | 12.99 | 812  | 2.1788          | 0.2329 | 0.1098 | 0.1922 | 0.2187    |
| 2.4194        | 14.0  | 875  | 2.1517          | 0.2336 | 0.1087 | 0.1919 | 0.2188    |
| 2.3908        | 14.99 | 937  | 2.1290          | 0.2343 | 0.109  | 0.1918 | 0.2195    |
| 2.3657        | 16.0  | 1000 | 2.1060          | 0.2324 | 0.107  | 0.1895 | 0.2175    |
| 2.3215        | 16.99 | 1062 | 2.0887          | 0.232  | 0.1066 | 0.1895 | 0.2171    |
| 2.3236        | 18.0  | 1125 | 2.0746          | 0.2328 | 0.1075 | 0.1899 | 0.2181    |
| 2.3018        | 18.99 | 1187 | 2.0612          | 0.2337 | 0.1067 | 0.1898 | 0.2183    |
| 2.2788        | 20.0  | 1250 | 2.0500          | 0.2337 | 0.1071 | 0.1901 | 0.2187    |
| 2.2502        | 20.99 | 1312 | 2.0406          | 0.2338 | 0.1072 | 0.1897 | 0.2187    |
| 2.2652        | 22.0  | 1375 | 2.0317          | 0.2339 | 0.1072 | 0.1898 | 0.2188    |
| 2.2508        | 22.99 | 1437 | 2.0253          | 0.2332 | 0.1069 | 0.1891 | 0.2181    |
| 2.2233        | 24.0  | 1500 | 2.0192          | 0.235  | 0.1087 | 0.1908 | 0.2202    |
| 2.2225        | 24.99 | 1562 | 2.0144          | 0.2352 | 0.1095 | 0.1912 | 0.2202    |
| 2.2248        | 26.0  | 1625 | 2.0107          | 0.2353 | 0.1094 | 0.1915 | 0.2204    |
| 2.235         | 26.99 | 1687 | 2.0075          | 0.235  | 0.1092 | 0.1915 | 0.2201    |
| 2.1964        | 28.0  | 1750 | 2.0056          | 0.2359 | 0.1096 | 0.1917 | 0.2209    |
| 2.1996        | 28.99 | 1812 | 2.0047          | 0.2361 | 0.11   | 0.192  | 0.2212    |
| 2.2228        | 29.76 | 1860 | 2.0045          | 0.2361 | 0.11   | 0.192  | 0.2212    |


### Framework versions

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