readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-finetuned-cnndm_fs0.1-c
    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-finetuned-cnndm_fs0.1-c
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9852
  - Recall: 34.0438
  - Precision: 33.1906
  - F1: 31.9429
  - Gen Len: 18.9962
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 1799
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Recall  | Precision | F1      | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.19          | 0.11  | 200  | 1.6689          | 33.0433 | 41.8436   | 35.485  | 18.9695 |
  | 1.74          | 0.23  | 400  | 1.5476          | 36.2979 | 44.1939   | 38.3491 | 18.9741 |
  | 1.6352        | 0.34  | 600  | 1.5075          | 33.8389 | 42.4269   | 36.2306 | 18.9848 |
  | 1.5937        | 0.46  | 800  | 1.4779          | 33.8957 | 42.3366   | 36.2976 | 18.9939 |
  | 1.5457        | 0.57  | 1000 | 1.4497          | 34.2432 | 42.4519   | 36.5314 | 18.9916 |
  | 1.522         | 0.69  | 1200 | 1.4360          | 34.8509 | 42.6855   | 36.9827 | 18.9886 |
  | 1.5091        | 0.8   | 1400 | 1.4210          | 34.5935 | 42.3167   | 36.7092 | 18.9848 |
  | 1.5015        | 0.92  | 1600 | 1.4013          | 35.3025 | 43.1577   | 37.4461 | 18.9954 |
  | 1.4897        | 1.03  | 1800 | 1.3980          | 34.498  | 42.2453   | 36.5759 | 18.9886 |
  | 1.468         | 1.15  | 2000 | 1.3998          | 34.6134 | 42.053    | 36.5715 | 18.9863 |
  | 1.4812        | 1.26  | 2200 | 1.4014          | 34.5802 | 41.9303   | 36.5025 | 18.9871 |
  | 1.5264        | 1.38  | 2400 | 1.4729          | 34.0632 | 40.792    | 35.5837 | 18.9863 |
  | 1.7346        | 1.49  | 2600 | 1.6945          | 33.8488 | 36.3411   | 33.3566 | 18.997  |
  | 1.9477        | 1.61  | 2800 | 1.8588          | 34.0827 | 34.8631   | 32.749  | 18.9931 |
  | 2.1295        | 1.72  | 3000 | 1.9741          | 34.6842 | 33.8048   | 32.5274 | 18.9939 |
  | 2.1759        | 1.84  | 3200 | 1.9805          | 34.4333 | 33.5371   | 32.2921 | 18.9962 |
  | 2.194         | 1.95  | 3400 | 1.9852          | 34.0438 | 33.1906   | 31.9429 | 18.9962 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  