update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- un_multi
+metrics:
+- bleu
+model-index:
+- name: m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: un_multi
+      type: un_multi
+      args: ar-en
+    metrics:
+    - name: Bleu
+      type: bleu
+      value: 41.8577
+---
+
+<!-- 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. -->
+
+# m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
+
+This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the un_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3603
+- Bleu: 41.8577
+- Meteor: 0.4199
+- Gen Len: 41.9
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 11
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
+| 5.111         | 0.5   | 100  | 3.2467          | 29.5017 | 0.3371 | 42.425  |
+| 2.1491        | 1.0   | 200  | 1.0018          | 33.0563 | 0.3593 | 41.205  |
+| 0.5911        | 1.5   | 300  | 0.4159          | 34.5818 | 0.3705 | 42.0625 |
+| 0.3546        | 2.0   | 400  | 0.3723          | 36.6179 | 0.3823 | 40.925  |
+| 0.2487        | 2.5   | 500  | 0.3595          | 39.0331 | 0.3956 | 41.56   |
+| 0.2365        | 3.0   | 600  | 0.3485          | 39.5188 | 0.4023 | 41.6425 |
+| 0.1687        | 3.5   | 700  | 0.3542          | 40.1728 | 0.4043 | 42.61   |
+| 0.1791        | 4.0   | 800  | 0.3466          | 40.4858 | 0.4101 | 41.5575 |
+| 0.1196        | 4.5   | 900  | 0.3493          | 41.2457 | 0.4123 | 41.755  |
+| 0.1394        | 5.0   | 1000 | 0.3486          | 40.5606 | 0.4114 | 41.78   |
+| 0.0958        | 5.5   | 1100 | 0.3568          | 41.1873 | 0.4157 | 41.7275 |
+| 0.1043        | 6.0   | 1200 | 0.3557          | 41.2749 | 0.4165 | 41.935  |
+| 0.073         | 6.5   | 1300 | 0.3603          | 41.8577 | 0.4199 | 41.9    |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1