readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mtop
  model-index:
  - name: t5-base-adv-mtop
    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-adv-mtop
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the mtop dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1009
  - Exact Match: 0.7937
  
  ## 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: 0.001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 64
  - total_train_batch_size: 512
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 3000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Exact Match |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 4.2521        | 1.09  | 200  | 0.1367          | 0.5418      |
  | 6.2586        | 2.17  | 400  | 0.1020          | 0.6004      |
  | 4.0003        | 3.26  | 600  | 0.1009          | 0.6179      |
  | 2.7191        | 4.35  | 800  | 0.1066          | 0.6251      |
  | 1.5031        | 5.43  | 1000 | 0.1215          | 0.6286      |
  | 0.703         | 6.52  | 1200 | 0.1238          | 0.6215      |
  | 0.6371        | 7.61  | 1400 | 0.1365          | 0.6286      |
  | 0.3712        | 8.69  | 1600 | 0.1450          | 0.6300      |
  | 0.5666        | 9.78  | 1800 | 0.1500          | 0.6295      |
  | 0.5237        | 10.87 | 2000 | 0.1416          | 0.6251      |
  | 0.4562        | 11.96 | 2200 | 0.1464          | 0.6313      |
  | 0.3421        | 13.04 | 2400 | 0.1635          | 0.6277      |
  | 0.3686        | 14.13 | 2600 | 0.1643          | 0.6322      |
  | 0.218         | 15.22 | 2800 | 0.1800          | 0.6277      |
  | 0.2371        | 16.3  | 3000 | 0.1742          | 0.6268      |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  