readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - recall
  - precision
  - f1
  model-index:
  - name: t5-base-finetuned-cnndm_fs0.2-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_fs0.2-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: 2.8786
  - Recall: 45.182
  - Precision: 45.6366
  - F1: 43.5272
  - Gen Len: 19.0
  
  ## 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: 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:-------:|:-------:|
  | 2.2433        | 0.06  | 200  | 1.6617          | 34.7989 | 43.1652   | 36.9039 | 18.9726 |
  | 1.7621        | 0.11  | 400  | 1.5553          | 34.8459 | 42.7785   | 36.8818 | 18.9855 |
  | 1.6867        | 0.17  | 600  | 1.4956          | 34.5984 | 42.913    | 36.8249 | 18.9909 |
  | 1.6149        | 0.23  | 800  | 1.4543          | 34.9504 | 42.6459   | 37.0426 | 18.9855 |
  | 1.5851        | 0.29  | 1000 | 1.4334          | 35.7001 | 43.5023   | 37.7777 | 18.9924 |
  | 1.5671        | 0.34  | 1200 | 1.4197          | 36.373  | 44.4379   | 38.5734 | 18.9886 |
  | 1.5541        | 0.4   | 1400 | 1.4013          | 35.7014 | 44.0427   | 37.9594 | 18.9886 |
  | 1.5249        | 0.46  | 1600 | 1.3893          | 35.8985 | 44.1804   | 38.1521 | 18.9954 |
  | 1.5132        | 0.52  | 1800 | 1.3791          | 35.6578 | 44.2902   | 37.9697 | 18.9939 |
  | 1.5026        | 0.57  | 2000 | 1.3775          | 35.4521 | 43.9066   | 37.75   | 18.9931 |
  | 1.4593        | 0.63  | 2200 | 1.3720          | 35.9259 | 44.8208   | 38.3731 | 18.9954 |
  | 1.4898        | 0.69  | 2400 | 1.3684          | 35.8312 | 44.7705   | 38.3382 | 18.9954 |
  | 1.4653        | 0.75  | 2600 | 1.3479          | 35.9541 | 43.782    | 37.9422 | 18.9878 |
  | 1.4873        | 0.8   | 2800 | 1.3715          | 34.8075 | 42.2571   | 36.6352 | 18.9886 |
  | 1.5688        | 0.86  | 3000 | 1.4307          | 35.9238 | 43.3122   | 37.831  | 18.9848 |
  | 1.6447        | 0.92  | 3200 | 1.5962          | 35.8068 | 40.2078   | 36.3341 | 18.9916 |
  | 2.0956        | 0.98  | 3400 | 2.0504          | 37.9871 | 35.7888   | 35.2125 | 19.0    |
  | 2.6014        | 1.03  | 3600 | 2.4071          | 39.1808 | 35.1042   | 35.4575 | 19.0    |
  | 2.9256        | 1.09  | 3800 | 2.6465          | 38.5632 | 35.3377   | 35.3861 | 19.0    |
  | 3.152         | 1.15  | 4000 | 2.8162          | 39.8996 | 38.9274   | 37.832  | 19.0    |
  | 3.3873        | 1.21  | 4200 | 2.9517          | 40.1783 | 42.1101   | 39.5447 | 19.0    |
  | 3.5098        | 1.26  | 4400 | 3.0453          | 39.7718 | 42.8675   | 39.7276 | 19.0    |
  | 3.6404        | 1.32  | 4600 | 3.1491          | 38.5347 | 42.765    | 39.0569 | 19.0    |
  | 3.7581        | 1.38  | 4800 | 3.2215          | 38.1938 | 42.8759   | 38.8667 | 19.0    |
  | 3.8092        | 1.43  | 5000 | 3.2311          | 38.3427 | 43.0885   | 38.888  | 19.0    |
  | 3.7752        | 1.49  | 5200 | 2.9680          | 42.6082 | 45.7346   | 42.3256 | 18.9909 |
  | 3.1818        | 1.55  | 5400 | 2.6873          | 46.0617 | 46.2819   | 44.1101 | 18.9909 |
  | 3.0866        | 1.61  | 5600 | 2.6852          | 44.5548 | 44.6688   | 42.6192 | 18.9909 |
  | 3.1263        | 1.66  | 5800 | 2.7389          | 45.6774 | 45.3637   | 43.4265 | 18.9863 |
  | 3.1999        | 1.72  | 6000 | 2.7845          | 45.9305 | 45.851    | 43.8446 | 18.9909 |
  | 3.261         | 1.78  | 6200 | 2.8133          | 46.0089 | 46.0445   | 44.0406 | 18.9909 |
  | 3.3025        | 1.84  | 6400 | 2.8447          | 45.9561 | 46.1086   | 44.03   | 18.9909 |
  | 3.3431        | 1.89  | 6600 | 2.8645          | 46.0489 | 46.0915   | 44.0899 | 19.0    |
  | 3.3625        | 1.95  | 6800 | 2.8786          | 45.182  | 45.6366   | 43.5272 | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu111
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  