transformers tensorboard safetensors led text2text-generation summarization generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
tags:
- summarization
- generated_from_trainer
model-index:
- name: led-risalah_data_v4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# led-risalah_data_v4

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6965
- Rouge1 Precision: 0.7537
- Rouge1 Recall: 0.2044
- Rouge1 Fmeasure: 0.3201

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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 Fmeasure | Rouge1 Precision | Rouge1 Recall |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:----------------:|:-------------:|
| 2.4649        | 0.91  | 8    | 1.9501          | 0.2231          | 0.5607           | 0.1407        |
| 1.7599        | 1.94  | 17   | 1.7553          | 0.2741          | 0.657            | 0.1746        |
| 1.4655        | 2.97  | 26   | 1.6912          | 0.2786          | 0.6685           | 0.1774        |
| 1.2734        | 4.0   | 35   | 1.7006          | 0.2589          | 0.651            | 0.162         |
| 1.2852        | 4.91  | 43   | 1.6481          | 0.2733          | 0.6657           | 0.1732        |
| 1.1964        | 5.94  | 52   | 1.6380          | 0.263           | 0.6567           | 0.1655        |
| 1.108         | 6.97  | 61   | 1.6441          | 0.2766          | 0.6757           | 0.1746        |
| 1.1023        | 8.91  | 72   | 1.1080          | 0.2842          | 0.6932           | 0.1794        |
| 1.2354        | 9.94  | 81   | 1.1105          | 0.2816          | 0.6858           | 0.1779        |
| 1.1152        | 10.97 | 90   | 1.1317          | 0.2872          | 0.71             | 0.1804        |
| 1.17          | 12.0  | 99   | 1.1206          | 0.2896          | 0.6942           | 0.1837        |
| 1.0691        | 12.91 | 107  | 1.1037          | 0.2941          | 0.7234           | 0.1851        |
| 0.9594        | 13.94 | 116  | 1.1145          | 0.2983          | 0.7299           | 0.1879        |
| 1.0332        | 14.97 | 125  | 1.1295          | 0.2959          | 0.7243           | 0.1863        |
| 0.9519        | 16.0  | 134  | 1.1271          | 0.2916          | 0.7114           | 0.1839        |
| 0.8779        | 16.91 | 142  | 1.1314          | 0.2971          | 0.7192           | 0.1878        |
| 0.944         | 18.91 | 152  | 0.8427          | 0.3212          | 0.7799           | 0.2036        |
| 0.9652        | 19.94 | 161  | 0.8398          | 0.3075          | 0.7396           | 0.1951        |
| 0.9622        | 20.97 | 170  | 0.8421          | 0.3255          | 0.7776           | 0.207         |
| 0.9645        | 22.0  | 179  | 0.8550          | 0.3045          | 0.7283           | 0.1934        |
| 0.8923        | 22.91 | 187  | 0.8556          | 0.3145          | 0.7585           | 0.1992        |
| 0.8635        | 23.94 | 196  | 0.8622          | 0.3086          | 0.7445           | 0.1957        |
| 0.827         | 24.97 | 205  | 0.8648          | 0.3047          | 0.7358           | 0.193         |
| 0.8529        | 26.0  | 214  | 0.8650          | 0.3129          | 0.7586           | 0.1981        |
| 0.7505        | 26.91 | 222  | 0.8719          | 0.3135          | 0.7591           | 0.1985        |
| 0.7491        | 27.94 | 231  | 0.8710          | 0.3078          | 0.7419           | 0.1951        |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1
