readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-1feb-2
    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-1feb-2
  
  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: 2.3856
  - Rouge1: 8.74
  - Rouge2: 2.66
  - Rougel: 8.58
  - Rougelsum: 8.6
  
  ## 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: 0.0001
  - 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: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | 5.3153        | 1.0   | 311  | 2.6946          | 7.56   | 2.04   | 7.55   | 7.46      |
  | 3.3159        | 2.0   | 622  | 2.5923          | 8.07   | 2.28   | 8.05   | 8.02      |
  | 3.092         | 3.0   | 933  | 2.5342          | 7.83   | 2.01   | 7.81   | 7.76      |
  | 2.9676        | 4.0   | 1244 | 2.4982          | 8.45   | 2.49   | 8.37   | 8.39      |
  | 2.862         | 5.0   | 1555 | 2.4627          | 8.3    | 2.5    | 8.26   | 8.27      |
  | 2.7891        | 6.0   | 1866 | 2.4366          | 8.67   | 2.81   | 8.53   | 8.55      |
  | 2.7391        | 7.0   | 2177 | 2.4215          | 8.51   | 2.54   | 8.45   | 8.42      |
  | 2.6887        | 8.0   | 2488 | 2.4277          | 8.71   | 2.53   | 8.56   | 8.54      |
  | 2.6392        | 9.0   | 2799 | 2.3939          | 8.49   | 2.53   | 8.4    | 8.4       |
  | 2.6139        | 10.0  | 3110 | 2.4015          | 9.28   | 2.85   | 9.14   | 9.19      |
  | 2.5727        | 11.0  | 3421 | 2.3956          | 9.24   | 2.9    | 9.08   | 9.09      |
  | 2.5595        | 12.0  | 3732 | 2.3856          | 8.45   | 2.59   | 8.31   | 8.35      |
  | 2.5471        | 13.0  | 4043 | 2.3891          | 8.64   | 2.79   | 8.53   | 8.52      |
  | 2.5231        | 14.0  | 4354 | 2.3870          | 8.78   | 2.79   | 8.64   | 8.6       |
  | 2.5024        | 15.0  | 4665 | 2.3856          | 8.74   | 2.66   | 8.58   | 8.6       |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  