readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: t5-base-mse-summarization
    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. -->
  
  # t5-base-mse-summarization
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8743
  - Rouge1: 45.9597
  - Rouge2: 26.8086
  - Rougel: 39.935
  - Rougelsum: 43.8897
  - Bleurt: -0.7132
  - Gen Len: 18.464
  
  ## 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: 1e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleurt  | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
  | 1.2568        | 1.0   | 267  | 1.0472          | 41.6829 | 21.9654 | 35.4264 | 39.5556   | -0.8231 | 18.522  |
  | 1.1085        | 2.0   | 534  | 0.9840          | 43.1479 | 23.3351 | 36.9244 | 40.886    | -0.7843 | 18.534  |
  | 1.0548        | 3.0   | 801  | 0.9515          | 44.1511 | 24.4912 | 37.9549 | 41.9984   | -0.7702 | 18.528  |
  | 1.0251        | 4.0   | 1068 | 0.9331          | 44.426  | 24.9439 | 38.2978 | 42.1731   | -0.7633 | 18.619  |
  | 0.9888        | 5.0   | 1335 | 0.9201          | 45.0385 | 25.524  | 38.8681 | 42.8998   | -0.7497 | 18.523  |
  | 0.9623        | 6.0   | 1602 | 0.9119          | 44.8648 | 25.469  | 38.9281 | 42.7798   | -0.7496 | 18.537  |
  | 0.9502        | 7.0   | 1869 | 0.9015          | 44.9668 | 25.5041 | 38.9463 | 42.9368   | -0.7412 | 18.48   |
  | 0.9316        | 8.0   | 2136 | 0.8973          | 45.3028 | 25.7232 | 39.1533 | 43.277    | -0.7318 | 18.523  |
  | 0.9191        | 9.0   | 2403 | 0.8921          | 45.2901 | 25.916  | 39.2909 | 43.3022   | -0.7296 | 18.529  |
  | 0.9122        | 10.0  | 2670 | 0.8889          | 45.3535 | 26.1369 | 39.4861 | 43.28     | -0.7271 | 18.545  |
  | 0.8993        | 11.0  | 2937 | 0.8857          | 45.5345 | 26.1669 | 39.5656 | 43.4664   | -0.7269 | 18.474  |
  | 0.8905        | 12.0  | 3204 | 0.8816          | 45.7796 | 26.4145 | 39.8117 | 43.734    | -0.7185 | 18.503  |
  | 0.8821        | 13.0  | 3471 | 0.8794          | 45.7163 | 26.4314 | 39.719  | 43.6407   | -0.7211 | 18.496  |
  | 0.8789        | 14.0  | 3738 | 0.8784          | 45.9097 | 26.7281 | 39.9071 | 43.8105   | -0.7127 | 18.452  |
  | 0.8665        | 15.0  | 4005 | 0.8765          | 46.1148 | 26.8882 | 40.1006 | 43.988    | -0.711  | 18.443  |
  | 0.8676        | 16.0  | 4272 | 0.8766          | 45.9119 | 26.7674 | 39.9001 | 43.8237   | -0.718  | 18.491  |
  | 0.8637        | 17.0  | 4539 | 0.8758          | 45.9158 | 26.7153 | 39.9463 | 43.8323   | -0.7183 | 18.492  |
  | 0.8622        | 18.0  | 4806 | 0.8752          | 45.9508 | 26.75   | 39.9533 | 43.8795   | -0.7144 | 18.465  |
  | 0.8588        | 19.0  | 5073 | 0.8744          | 45.9192 | 26.7352 | 39.8921 | 43.8204   | -0.7148 | 18.462  |
  | 0.8554        | 20.0  | 5340 | 0.8743          | 45.9597 | 26.8086 | 39.935  | 43.8897   | -0.7132 | 18.464  |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  