readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-18jan-3
    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. -->
  
  # mt5-small-finetuned-18jan-3
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.6115
  - Rouge1: 7.259
  - Rouge2: 0.3667
  - Rougel: 7.1595
  - Rougelsum: 7.156
  
  ## 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: 0.0002
  - train_batch_size: 10
  - eval_batch_size: 10
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 7.1947        | 1.0   | 60   | 3.1045          | 5.91   | 0.8583 | 5.8687 | 5.8123    |
  | 3.8567        | 2.0   | 120  | 2.7744          | 8.0065 | 0.4524 | 8.0204 | 7.85      |
  | 3.4346        | 3.0   | 180  | 2.7319          | 7.5954 | 0.4524 | 7.5204 | 7.4833    |
  | 3.219         | 4.0   | 240  | 2.6736          | 8.5329 | 0.3333 | 8.487  | 8.312     |
  | 3.0836        | 5.0   | 300  | 2.6583          | 8.3405 | 0.5667 | 8.2003 | 8.0543    |
  | 2.9713        | 6.0   | 360  | 2.6516          | 8.8421 | 0.1667 | 8.7597 | 8.6754    |
  | 2.9757        | 7.0   | 420  | 2.6369          | 8.04   | 0.3667 | 8.0018 | 7.8489    |
  | 2.8321        | 8.0   | 480  | 2.6215          | 6.8739 | 0.3667 | 6.859  | 6.7917    |
  | 2.794         | 9.0   | 540  | 2.6090          | 7.0738 | 0.4167 | 7.0232 | 6.9619    |
  | 2.7695        | 10.0  | 600  | 2.6115          | 7.259  | 0.3667 | 7.1595 | 7.156     |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  