readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mtop
  model-index:
  - name: t5-base-pointer-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-pointer-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: 0.1281
  - Exact Match: 0.7105
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 1.7704        | 1.09  | 200  | 0.3664          | 0.1315      |
  | 1.9751        | 2.17  | 400  | 0.2091          | 0.3400      |
  | 1.0019        | 3.26  | 600  | 0.1453          | 0.4586      |
  | 1.313         | 4.35  | 800  | 0.1313          | 0.5065      |
  | 0.6593        | 5.43  | 1000 | 0.1281          | 0.5266      |
  | 0.3216        | 6.52  | 1200 | 0.1317          | 0.5253      |
  | 0.4614        | 7.61  | 1400 | 0.1508          | 0.5262      |
  | 0.3577        | 8.69  | 1600 | 0.1422          | 0.5360      |
  | 0.3748        | 9.78  | 1800 | 0.1419          | 0.5459      |
  | 0.2422        | 10.87 | 2000 | 0.1603          | 0.5356      |
  | 0.4443        | 11.96 | 2200 | 0.1526          | 0.5472      |
  | 0.2671        | 13.04 | 2400 | 0.1606          | 0.5481      |
  | 0.227         | 14.13 | 2600 | 0.1774          | 0.5441      |
  | 0.2053        | 15.22 | 2800 | 0.1752          | 0.5441      |
  | 0.1517        | 16.3  | 3000 | 0.1770          | 0.5481      |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  