Zohaib002/Longformer-Encoder-Decoder-LED

1---2license: bsd-3-clause3base_model: pszemraj/led-base-book-summary4tags:5- generated_from_trainer6metrics:7- rouge8model-index:9- name: device10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# device17 18This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the None dataset.19It achieves the following results on the evaluation set:20- Loss: 1.024721- Rouge1: 0.626922- Rouge2: 0.392123- Rougel: 0.526124- Rougelsum: 0.526625- Gen Len: 67.558426 27## Model description28 29More information needed30 31## Intended uses & limitations32 33More information needed34 35## Training and evaluation data36 37More information needed38 39## Training procedure40 41### Training hyperparameters42 43The following hyperparameters were used during training:44- learning_rate: 2e-0545- train_batch_size: 846- eval_batch_size: 847- seed: 4248- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0849- lr_scheduler_type: linear50- num_epochs: 851- mixed_precision_training: Native AMP52 53### Training results54 55| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |56|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|57| No log        | 1.0   | 274  | 1.0933          | 0.5918 | 0.3356 | 0.4785 | 0.4788    | 72.0547 |58| 1.1731        | 2.0   | 548  | 1.0177          | 0.5985 | 0.3525 | 0.4902 | 0.4906    | 68.5055 |59| 1.1731        | 3.0   | 822  | 0.9976          | 0.6063 | 0.3603 | 0.4982 | 0.4982    | 69.7263 |60| 0.7216        | 4.0   | 1096 | 0.9922          | 0.6113 | 0.3735 | 0.5081 | 0.5084    | 68.1861 |61| 0.7216        | 5.0   | 1370 | 0.9957          | 0.6193 | 0.3826 | 0.5216 | 0.5217    | 65.4617 |62| 0.5252        | 6.0   | 1644 | 1.0127          | 0.6252 | 0.3877 | 0.5231 | 0.5236    | 68.0584 |63| 0.5252        | 7.0   | 1918 | 1.0221          | 0.6252 | 0.3897 | 0.5246 | 0.5246    | 67.5931 |64| 0.4079        | 8.0   | 2192 | 1.0247          | 0.6269 | 0.3921 | 0.5261 | 0.5266    | 67.5584 |65 66 67### Framework versions68 69- Transformers 4.42.470- Pytorch 2.3.1+cu12171- Datasets 2.20.072- Tokenizers 0.19.173