Update README.md

README.md

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----
-base_model: UBC-NLP/AraT5v2-base-1024
-tags:
-- generated_from_trainer
-datasets:
-- opus100
-metrics:
-- bleu
-model-index:
-- name: finetune-t5-base-on-opus100-Ar2En-without-optimization
-  results:
-  - task:
-      name: Sequence-to-sequence Language Modeling
-      type: text2text-generation
-    dataset:
-      name: opus100
-      type: opus100
-      config: ar-en
-      split: train[:7000]
-      args: ar-en
-    metrics:
-    - name: Bleu
-      type: bleu
-      value: 10.4288
----
-
-<!-- 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. -->
-
-# finetune-t5-base-on-opus100-Ar2En-without-optimization
-
-This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on the opus100 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 3.0042
-- Bleu: 10.4288
-- Gen Len: 10.739
-
-## 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: 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: 18
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
-| 10.1448       | 1.0   | 210  | 3.9256          | 2.8335  | 9.4988  |
-| 4.9822        | 2.0   | 420  | 3.5760          | 4.9001  | 10.3329 |
-| 4.42          | 3.0   | 630  | 3.4037          | 5.6973  | 10.301  |
-| 4.1414        | 4.0   | 840  | 3.3057          | 6.5224  | 10.5559 |
-| 3.9451        | 5.0   | 1050 | 3.2169          | 7.409   | 10.7571 |
-| 3.7972        | 6.0   | 1260 | 3.1759          | 8.1445  | 10.5908 |
-| 3.6687        | 7.0   | 1470 | 3.1340          | 8.246   | 10.7451 |
-| 3.5494        | 8.0   | 1680 | 3.1098          | 8.5656  | 10.7616 |
-| 3.4748        | 9.0   | 1890 | 3.0749          | 9.052   | 10.8798 |
-| 3.3945        | 10.0  | 2100 | 3.0725          | 9.3223  | 10.6794 |
-| 3.314         | 11.0  | 2310 | 3.0511          | 9.67    | 10.6871 |
-| 3.2606        | 12.0  | 2520 | 3.0398          | 9.6105  | 10.6531 |
-| 3.2314        | 13.0  | 2730 | 3.0211          | 10.0661 | 10.752  |
-| 3.1557        | 14.0  | 2940 | 3.0188          | 10.0724 | 10.7188 |
-| 3.1571        | 15.0  | 3150 | 3.0148          | 10.3648 | 10.7596 |
-| 3.1213        | 16.0  | 3360 | 3.0061          | 10.4008 | 10.7784 |
-| 3.1111        | 17.0  | 3570 | 3.0077          | 10.4588 | 10.7155 |
-| 3.0851        | 18.0  | 3780 | 3.0042          | 10.4288 | 10.739  |
-
-
-### Framework versions
-
-- Transformers 4.35.2
-- Pytorch 2.0.0
-- Datasets 2.1.0
-- Tokenizers 0.15.0