readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - cstop_artificial
  model-index:
  - name: t5-base-pointer-adv-cstop_artificial
    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-cstop_artificial
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the cstop_artificial dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0728
  - Exact Match: 0.7925
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 1.7423        | 12.5  | 200  | 0.1173          | 0.2397      |
  | 0.3678        | 25.0  | 400  | 0.0728          | 0.3363      |
  | 0.3202        | 37.5  | 600  | 0.0879          | 0.3381      |
  | 0.3452        | 50.0  | 800  | 0.0908          | 0.3363      |
  | 0.3099        | 62.5  | 1000 | 0.1056          | 0.3435      |
  | 0.3057        | 75.0  | 1200 | 0.1109          | 0.3470      |
  | 0.3045        | 87.5  | 1400 | 0.1273          | 0.3453      |
  | 0.3052        | 100.0 | 1600 | 0.1065          | 0.3417      |
  | 0.3037        | 112.5 | 1800 | 0.1387          | 0.3381      |
  | 0.3036        | 125.0 | 2000 | 0.1421          | 0.3453      |
  | 0.3023        | 137.5 | 2200 | 0.1649          | 0.3399      |
  | 0.3028        | 150.0 | 2400 | 0.1574          | 0.3399      |
  | 0.3025        | 162.5 | 2600 | 0.1563          | 0.3399      |
  | 0.3017        | 175.0 | 2800 | 0.1589          | 0.3399      |
  | 0.302         | 187.5 | 3000 | 0.1587          | 0.3417      |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  