readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: led-base-16384-100-MDS
    results: []
  ---
  
  <!-- 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. -->
  
  # led-base-16384-100-MDS
  
  This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.1425
  - Rouge1: 16.7324
  - Rouge2: 5.8501
  - Rougel: 13.908
  - Rougelsum: 13.8469
  - Gen Len: 20.0
  
  ## 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: 4
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 25   | 3.6187          | 15.1426 | 4.2468 | 13.4488 | 13.38     | 20.0    |
  | No log        | 2.0   | 50   | 3.9873          | 13.4341 | 3.3283 | 10.2739 | 10.8229   | 20.0    |
  | No log        | 3.0   | 75   | 4.0264          | 18.1891 | 5.3395 | 15.0797 | 15.3586   | 20.0    |
  | No log        | 4.0   | 100  | 4.0929          | 17.0091 | 5.5336 | 14.4381 | 14.5149   | 19.5    |
  | No log        | 5.0   | 125  | 4.1425          | 16.7324 | 5.8501 | 13.908  | 13.8469   | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.2
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  