Final implementation

README.md

@@ -13,13 +13,16 @@ model-index:
 <!-- 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. -->
 
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/boghdady95/huggingface/runs/i9kdffyd)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/boghdady95/huggingface/runs/i9kdffyd)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/boghdady95/huggingface/runs/i9kdffyd)
 # ar-en-model
 
 This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2988
-- Bleu: 31.7475
-- Gen Len: 33.5269
+- Loss: 0.1237
+- Bleu: 61.7434
+- Gen Len: 31.2413
 
 ## Model description
 
@@ -44,28 +47,21 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 3
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
-| No log        | 1.0   | 312  | 0.3562          | 25.2145 | 33.397  |
-| 0.6311        | 2.0   | 624  | 0.3311          | 27.4389 | 32.9487 |
-| 0.6311        | 3.0   | 936  | 0.3178          | 28.887  | 33.6215 |
-| 0.2523        | 4.0   | 1248 | 0.3102          | 29.9143 | 33.648  |
-| 0.219         | 5.0   | 1560 | 0.3057          | 30.6256 | 33.4651 |
-| 0.219         | 6.0   | 1872 | 0.3028          | 30.9421 | 33.4459 |
-| 0.2025        | 7.0   | 2184 | 0.3008          | 31.5297 | 33.8605 |
-| 0.2025        | 8.0   | 2496 | 0.2996          | 31.8919 | 33.8492 |
-| 0.1895        | 9.0   | 2808 | 0.2989          | 31.7071 | 33.854  |
-| 0.182         | 10.0  | 3120 | 0.2988          | 31.7475 | 33.5269 |
+| 0.1394        | 1.0   | 1250 | 0.1527          | 63.1436 | 30.9039 |
+| 0.1215        | 2.0   | 2500 | 0.1507          | 63.0988 | 30.8535 |
+| 0.1122        | 3.0   | 3750 | 0.1508          | 63.1177 | 30.8768 |
 
 
 ### Framework versions
 
 - Transformers 4.42.3
-- Pytorch 2.2.1+cu121
+- Pytorch 2.1.2
 - Datasets 2.20.0
 - Tokenizers 0.19.1

runs/Aug04_21-48-17_6a18a6ce128c/events.out.tfevents.1722808099.6a18a6ce128c.34.2

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