readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mt5-small-finetuned-xsum
    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-xsum
  
  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: 2.5196
  - Rouge1: 0.3378
  - Rouge2: 0.275
  - Rougel: 0.3372
  - Rougelsum: 0.3367
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
  | No log        | 1.0   | 21   | 11.8500         | 0.0    | 0.0    | 0.0    | 0.0       |
  | No log        | 2.0   | 42   | 11.1279         | 0.0    | 0.0    | 0.0    | 0.0       |
  | No log        | 3.0   | 63   | 10.0382         | 0.0    | 0.0    | 0.0    | 0.0       |
  | No log        | 4.0   | 84   | 9.1579          | 0.0    | 0.0    | 0.0    | 0.0       |
  | No log        | 5.0   | 105  | 8.6827          | 0.0    | 0.0    | 0.0    | 0.0       |
  | No log        | 6.0   | 126  | 7.3651          | 0.0028 | 0.0016 | 0.0028 | 0.0028    |
  | No log        | 7.0   | 147  | 6.4400          | 0.019  | 0.0129 | 0.0191 | 0.0197    |
  | No log        | 8.0   | 168  | 5.2631          | 0.0272 | 0.0229 | 0.0288 | 0.0288    |
  | No log        | 9.0   | 189  | 4.5832          | 0.1095 | 0.0688 | 0.1053 | 0.1051    |
  | No log        | 10.0  | 210  | 4.2350          | 0.1263 | 0.0824 | 0.1216 | 0.1235    |
  | No log        | 11.0  | 231  | 3.9249          | 0.1541 | 0.1051 | 0.1513 | 0.1532    |
  | No log        | 12.0  | 252  | 3.5469          | 0.1701 | 0.1156 | 0.1665 | 0.1683    |
  | No log        | 13.0  | 273  | 3.3689          | 0.2672 | 0.2095 | 0.2667 | 0.2659    |
  | No log        | 14.0  | 294  | 3.1733          | 0.3102 | 0.2483 | 0.3103 | 0.3104    |
  | No log        | 15.0  | 315  | 3.0810          | 0.3073 | 0.2457 | 0.3074 | 0.3071    |
  | No log        | 16.0  | 336  | 3.0005          | 0.3071 | 0.2451 | 0.3075 | 0.3069    |
  | No log        | 17.0  | 357  | 2.9663          | 0.3015 | 0.2364 | 0.3022 | 0.3018    |
  | No log        | 18.0  | 378  | 2.8718          | 0.3195 | 0.2583 | 0.3197 | 0.3187    |
  | No log        | 19.0  | 399  | 2.8061          | 0.3159 | 0.2554 | 0.316  | 0.3143    |
  | No log        | 20.0  | 420  | 2.7009          | 0.3351 | 0.273  | 0.3338 | 0.3341    |
  | No log        | 21.0  | 441  | 2.6307          | 0.3384 | 0.2763 | 0.3382 | 0.3381    |
  | No log        | 22.0  | 462  | 2.6006          | 0.3364 | 0.2743 | 0.3362 | 0.3357    |
  | No log        | 23.0  | 483  | 2.5819          | 0.3334 | 0.2712 | 0.3331 | 0.3333    |
  | 13.1102       | 24.0  | 504  | 2.5606          | 0.3309 | 0.269  | 0.3302 | 0.3305    |
  | 13.1102       | 25.0  | 525  | 2.5458          | 0.338  | 0.2744 | 0.3369 | 0.3373    |
  | 13.1102       | 26.0  | 546  | 2.5366          | 0.3361 | 0.2715 | 0.3352 | 0.3352    |
  | 13.1102       | 27.0  | 567  | 2.5301          | 0.3413 | 0.2787 | 0.3408 | 0.3406    |
  | 13.1102       | 28.0  | 588  | 2.5236          | 0.341  | 0.2783 | 0.3402 | 0.3401    |
  | 13.1102       | 29.0  | 609  | 2.5206          | 0.3405 | 0.2779 | 0.3399 | 0.3397    |
  | 13.1102       | 30.0  | 630  | 2.5196          | 0.3378 | 0.275  | 0.3372 | 0.3367    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  