readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-29jan-1
    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-29jan-1
  
  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: 2.4883
  - Rouge1: 19.5044
  - Rouge2: 6.2046
  - Rougel: 19.3543
  - Rougelsum: 19.381
  
  ## 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 6.4829        | 1.0   | 217  | 2.7590          | 12.7914 | 3.3267 | 12.493  | 12.4137   |
  | 3.4814        | 2.0   | 434  | 2.7229          | 16.7805 | 4.8009 | 16.4908 | 16.5233   |
  | 3.2161        | 3.0   | 651  | 2.6422          | 18.3488 | 5.0629 | 18.1397 | 18.1976   |
  | 3.045         | 4.0   | 868  | 2.6008          | 18.1363 | 5.7597 | 17.9056 | 17.9882   |
  | 2.9475        | 5.0   | 1085 | 2.6061          | 18.9355 | 6.0803 | 18.6355 | 18.7673   |
  | 2.8547        | 6.0   | 1302 | 2.5628          | 17.904  | 5.8618 | 17.7818 | 17.8446   |
  | 2.7685        | 7.0   | 1519 | 2.5311          | 18.9128 | 5.9625 | 18.7142 | 18.842    |
  | 2.705         | 8.0   | 1736 | 2.5371          | 19.6663 | 6.0395 | 19.3416 | 19.408    |
  | 2.6438        | 9.0   | 1953 | 2.5427          | 19.1516 | 6.0007 | 18.9663 | 19.0156   |
  | 2.6086        | 10.0  | 2170 | 2.5211          | 19.0945 | 6.4325 | 18.918  | 18.9664   |
  | 2.5394        | 11.0  | 2387 | 2.5226          | 18.9019 | 6.3004 | 18.7281 | 18.8082   |
  | 2.5004        | 12.0  | 2604 | 2.5136          | 18.9701 | 6.1868 | 18.7234 | 18.8098   |
  | 2.4666        | 13.0  | 2821 | 2.4958          | 18.155  | 6.1513 | 18.0758 | 18.1362   |
  | 2.4255        | 14.0  | 3038 | 2.5101          | 18.7561 | 6.2634 | 18.6477 | 18.7123   |
  | 2.3856        | 15.0  | 3255 | 2.4860          | 19.2239 | 6.4539 | 19.1162 | 19.1403   |
  | 2.3594        | 16.0  | 3472 | 2.4905          | 19.0075 | 6.1541 | 18.9106 | 18.9616   |
  | 2.3301        | 17.0  | 3689 | 2.4970          | 18.7102 | 6.2065 | 18.4881 | 18.5588   |
  | 2.3032        | 18.0  | 3906 | 2.4744          | 19.3199 | 6.6458 | 19.1365 | 19.1733   |
  | 2.2825        | 19.0  | 4123 | 2.4907          | 18.9608 | 6.3074 | 18.8124 | 18.8502   |
  | 2.2609        | 20.0  | 4340 | 2.4772          | 19.2785 | 6.4725 | 19.0379 | 19.0556   |
  | 2.2384        | 21.0  | 4557 | 2.4874          | 18.9376 | 6.2922 | 18.7618 | 18.8442   |
  | 2.2176        | 22.0  | 4774 | 2.4853          | 18.9962 | 6.2231 | 18.7551 | 18.7958   |
  | 2.2095        | 23.0  | 4991 | 2.4960          | 18.6517 | 5.8114 | 18.4809 | 18.4811   |
  | 2.1958        | 24.0  | 5208 | 2.4911          | 18.9743 | 6.2245 | 18.7692 | 18.869    |
  | 2.1777        | 25.0  | 5425 | 2.4788          | 18.9623 | 6.0877 | 18.7591 | 18.7917   |
  | 2.1645        | 26.0  | 5642 | 2.4883          | 19.2814 | 6.2264 | 19.1407 | 19.1835   |
  | 2.1575        | 27.0  | 5859 | 2.4910          | 19.4592 | 6.3513 | 19.2842 | 19.3017   |
  | 2.142         | 28.0  | 6076 | 2.4815          | 19.3045 | 6.2179 | 19.1271 | 19.1084   |
  | 2.1396        | 29.0  | 6293 | 2.4858          | 19.4159 | 6.275  | 19.2582 | 19.2731   |
  | 2.1438        | 30.0  | 6510 | 2.4883          | 19.5044 | 6.2046 | 19.3543 | 19.381    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  