readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - precision
  - recall
  model-index:
  - name: t5-test
    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-test
  
  This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0875
  - Gen Len: 2.4810
  - F1: 0.6349
  - Precision: 0.7576
  - Recall: 0.6114
  
  ## 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: 0.0003
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Gen Len | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:---------:|:------:|
  | 1.1787        | 0.59  | 250  | 0.1979          | 8.0     | 0.1757 | 0.1361    | 0.3077 |
  | 0.2061        | 1.18  | 500  | 0.1432          | 3.2532  | 0.3421 | 0.3855    | 0.3656 |
  | 0.161         | 1.77  | 750  | 0.1152          | 2.4177  | 0.5044 | 0.5949    | 0.5067 |
  | 0.1352        | 2.36  | 1000 | 0.1030          | 1.5063  | 0.4762 | 0.7722    | 0.3861 |
  | 0.1204        | 2.96  | 1250 | 0.0922          | 2.3291  | 0.6167 | 0.7487    | 0.5927 |
  | 0.1032        | 3.55  | 1500 | 0.0902          | 2.4810  | 0.6002 | 0.7008    | 0.5885 |
  | 0.095         | 4.14  | 1750 | 0.0887          | 2.4937  | 0.6338 | 0.7557    | 0.6119 |
  | 0.0912        | 4.73  | 2000 | 0.0875          | 2.4810  | 0.6349 | 0.7576    | 0.6114 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  