readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: flan-t5-large-da-multiwoz_fs0.1
    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. -->
  
  # flan-t5-large-da-multiwoz_fs0.1
  
  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3616
  - Accuracy: 40.8011
  - Num: 500
  - Gen Len: 15.662
  
  ## 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: 48
  - seed: 1799
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Num | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:-------:|
  | 1.7494        | 0.28  | 100  | 0.6287          | 21.9521  | 500 | 13.156  |
  | 0.7007        | 0.56  | 200  | 0.4876          | 31.5514  | 500 | 15.898  |
  | 0.5882        | 0.85  | 300  | 0.4478          | 33.6118  | 500 | 14.866  |
  | 0.5416        | 1.13  | 400  | 0.4258          | 34.729   | 500 | 14.902  |
  | 0.5125        | 1.41  | 500  | 0.4143          | 36.7116  | 500 | 15.314  |
  | 0.4893        | 1.69  | 600  | 0.4031          | 35.5287  | 500 | 14.516  |
  | 0.4878        | 1.97  | 700  | 0.3859          | 36.6642  | 500 | 15.586  |
  | 0.4596        | 2.25  | 800  | 0.3789          | 36.0323  | 500 | 14.898  |
  | 0.4536        | 2.54  | 900  | 0.3799          | 38.613   | 500 | 15.358  |
  | 0.439         | 2.82  | 1000 | 0.3760          | 39.1068  | 500 | 15.996  |
  | 0.438         | 3.1   | 1100 | 0.3651          | 39.6594  | 500 | 15.412  |
  | 0.4248        | 3.38  | 1200 | 0.3675          | 38.9787  | 500 | 15.052  |
  | 0.4186        | 3.66  | 1300 | 0.3659          | 39.5161  | 500 | 15.068  |
  | 0.4226        | 3.94  | 1400 | 0.3616          | 40.8011  | 500 | 15.662  |
  | 0.4163        | 4.23  | 1500 | 0.3626          | 40.5683  | 500 | 15.616  |
  | 0.4084        | 4.51  | 1600 | 0.3619          | 40.0144  | 500 | 15.728  |
  | 0.4189        | 4.79  | 1700 | 0.3596          | 39.7478  | 500 | 15.782  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  