update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+- rouge
+model-index:
+- name: mbart-large-50-English_German_Translation
+  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. -->
+
+# mbart-large-50-English_German_Translation
+
+This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2342
+- Bleu: 35.5931
+- Rouge: {'rouge1': 0.5803386608353808, 'rouge2': 0.3939141514072567, 'rougeL': 0.5438629663406402, 'rougeLsum': 0.544153348468965}
+- Meteor: {'meteor': 0.5500546034636025}
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Bleu    | Rouge                                                                                                                      | Meteor                         |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------------------------------------------------------------------------------------------------------------------:|:------------------------------:|
+| 1.7738        | 1.0   | 900  | 1.2342          | 35.7436 | {'rouge1': 0.5805815969432273, 'rouge2': 0.3941222478624937, 'rougeL': 0.544162316313326, 'rougeLsum': 0.5444260344836553} | {'meteor': 0.5511605039667078} |
+
+
+### Framework versions
+
+- Transformers 4.22.2
+- Pytorch 1.12.1
+- Datasets 2.5.2
+- Tokenizers 0.12.1