readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mtop
  model-index:
  - name: t5-small-pointer-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-small-pointer-mtop
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mtop dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1202
  - Exact Match: 0.7445
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 32
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 2.1451        | 6.65  | 200  | 0.5966          | 0.0134      |
  | 0.4695        | 13.33 | 400  | 0.2264          | 0.2998      |
  | 0.2229        | 19.98 | 600  | 0.1446          | 0.4649      |
  | 0.1389        | 26.65 | 800  | 0.1227          | 0.5154      |
  | 0.097         | 33.33 | 1000 | 0.1213          | 0.5221      |
  | 0.0724        | 39.98 | 1200 | 0.1202          | 0.5365      |
  | 0.0562        | 46.65 | 1400 | 0.1207          | 0.5436      |
  | 0.0457        | 53.33 | 1600 | 0.1240          | 0.5441      |
  | 0.0399        | 59.98 | 1800 | 0.1349          | 0.5441      |
  | 0.0317        | 66.65 | 2000 | 0.1369          | 0.5477      |
  | 0.0271        | 73.33 | 2200 | 0.1409          | 0.5490      |
  | 0.0237        | 79.98 | 2400 | 0.1462          | 0.5539      |
  | 0.0207        | 86.65 | 2600 | 0.1470          | 0.5517      |
  | 0.0188        | 93.33 | 2800 | 0.1505          | 0.5508      |
  | 0.0174        | 99.98 | 3000 | 0.1505          | 0.5512      |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  