readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - top_v2
  model-index:
  - name: t5-base-adv-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-base-adv-top_v2
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the top_v2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0336
  - Exact Match: 0.8540
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 64
  - total_train_batch_size: 256
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-----------:|
  | 1.4252        | 0.21  | 200  | 0.3381          | 0.1505      |
  | 0.4478        | 0.41  | 400  | 0.0673          | 0.3914      |
  | 0.38          | 0.62  | 600  | 0.0533          | 0.4060      |
  | 0.3603        | 0.82  | 800  | 0.0490          | 0.4132      |
  | 0.3539        | 1.03  | 1000 | 0.0420          | 0.4186      |
  | 0.3425        | 1.23  | 1200 | 0.0396          | 0.4219      |
  | 0.3373        | 1.44  | 1400 | 0.0384          | 0.4233      |
  | 0.3345        | 1.64  | 1600 | 0.0361          | 0.4247      |
  | 0.3334        | 1.85  | 1800 | 0.0357          | 0.4255      |
  | 0.33          | 2.05  | 2000 | 0.0361          | 0.4277      |
  | 0.3269        | 2.26  | 2200 | 0.0349          | 0.4278      |
  | 0.3262        | 2.46  | 2400 | 0.0345          | 0.4288      |
  | 0.324         | 2.67  | 2600 | 0.0342          | 0.4285      |
  | 0.3212        | 2.87  | 2800 | 0.0337          | 0.4295      |
  | 0.3257        | 3.08  | 3000 | 0.0336          | 0.4293      |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  