readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-18jan-7
    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-7
  
  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: 2.6070
  - Rouge1: 5.7833
  - Rouge2: 0.3333
  - Rougel: 5.7554
  - Rougelsum: 5.8833
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 7.6303        | 1.0   | 60   | 3.0842          | 6.2007 | 1.2374 | 6.1911 | 6.219     |
  | 3.8899        | 2.0   | 120  | 2.7540          | 7.7897 | 1.0    | 7.8183 | 7.8972    |
  | 3.4335        | 3.0   | 180  | 2.7391          | 8.3905 | 0.5333 | 8.4007 | 8.4989    |
  | 3.2524        | 4.0   | 240  | 2.6775          | 8.512  | 0.4167 | 8.5954 | 8.581     |
  | 3.0853        | 5.0   | 300  | 2.6776          | 7.6801 | 0.1667 | 7.7563 | 7.7873    |
  | 2.974         | 6.0   | 360  | 2.6641          | 8.2083 | 0.1667 | 8.3958 | 8.3792    |
  | 2.9018        | 7.0   | 420  | 2.6233          | 7.0679 | 0.3333 | 7.15   | 7.1833    |
  | 2.859         | 8.0   | 480  | 2.6238          | 6.5423 | 0.4167 | 6.5542 | 6.7       |
  | 2.8123        | 9.0   | 540  | 2.5961          | 6.3388 | 0.3333 | 6.2435 | 6.3902    |
  | 2.7843        | 10.0  | 600  | 2.6070          | 5.7833 | 0.3333 | 5.7554 | 5.8833    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  