silmi224/led-risalah_data_v13

1---2tags:3- summarization4- generated_from_trainer5model-index:6- name: led-risalah_data_v137  results: []8---9 10<!-- This model card has been generated automatically according to the information the Trainer had access to. You11should probably proofread and complete it, then remove this comment. -->12 13# led-risalah_data_v1314 15This model was trained from scratch on an unknown dataset.16It achieves the following results on the evaluation set:17- Loss: 1.519818- Rouge1 Precision: 0.418419- Rouge1 Recall: 0.403220- Rouge1 Fmeasure: 0.409221 22## Model description23 24More information needed25 26## Intended uses & limitations27 28More information needed29 30## Training and evaluation data31 32More information needed33 34## Training procedure35 36### Training hyperparameters37 38The following hyperparameters were used during training:39- learning_rate: 2e-0540- train_batch_size: 141- eval_batch_size: 142- seed: 4243- gradient_accumulation_steps: 444- total_train_batch_size: 445- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0846- lr_scheduler_type: linear47- num_epochs: 1048- mixed_precision_training: Native AMP49 50### Training results51 52| Training Loss | Epoch  | Step | Validation Loss | Rouge1 Fmeasure | Rouge1 Precision | Rouge1 Recall |53|:-------------:|:------:|:----:|:---------------:|:---------------:|:----------------:|:-------------:|54| 3.1517        | 0.9714 | 17   | 2.3560          | 0.2698          | 0.277            | 0.2642        |55| 2.2618        | 2.0    | 35   | 2.1487          | 0.3183          | 0.3295           | 0.3091        |56| 1.9714        | 2.9714 | 52   | 2.0826          | 0.3383          | 0.358            | 0.3226        |57| 1.8991        | 4.0    | 70   | 2.0284          | 0.34            | 0.3579           | 0.3248        |58| 1.7713        | 4.9714 | 87   | 1.9871          | 0.3667          | 0.3744           | 0.3602        |59| 1.7889        | 6.0    | 105  | 1.9714          | 0.3614          | 0.3729           | 0.3521        |60| 1.6378        | 6.9714 | 122  | 1.9481          | 0.3589          | 0.3762           | 0.3461        |61| 1.5649        | 8.0    | 140  | 1.9426          | 0.3657          | 0.3802           | 0.3545        |62| 1.5157        | 8.9714 | 157  | 1.9349          | 0.3667          | 0.375            | 0.361         |63 64 65### Framework versions66 67- Transformers 4.41.268- Pytorch 2.1.269- Datasets 2.19.270- Tokenizers 0.19.171