readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - top_v2
  model-index:
  - name: t5-small-pointer-top_v2
    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-top_v2
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the top_v2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0306
  - Exact Match: 0.8264
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 1.9316        | 0.82  | 200  | 0.4566          | 0.0084      |
  | 0.3713        | 1.65  | 400  | 0.1473          | 0.1230      |
  | 0.1747        | 2.47  | 600  | 0.0788          | 0.1984      |
  | 0.1104        | 3.29  | 800  | 0.0568          | 0.2149      |
  | 0.0842        | 4.12  | 1000 | 0.0473          | 0.2217      |
  | 0.0694        | 4.94  | 1200 | 0.0426          | 0.2260      |
  | 0.0603        | 5.76  | 1400 | 0.0383          | 0.2279      |
  | 0.0534        | 6.58  | 1600 | 0.0367          | 0.2281      |
  | 0.0477        | 7.41  | 1800 | 0.0347          | 0.2301      |
  | 0.0441        | 8.23  | 2000 | 0.0334          | 0.2314      |
  | 0.0413        | 9.05  | 2200 | 0.0323          | 0.2315      |
  | 0.0387        | 9.88  | 2400 | 0.0316          | 0.2316      |
  | 0.0366        | 10.7  | 2600 | 0.0311          | 0.2324      |
  | 0.0358        | 11.52 | 2800 | 0.0307          | 0.2324      |
  | 0.0343        | 12.35 | 3000 | 0.0306          | 0.2327      |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  