training end

README.md

@@ -12,14 +12,14 @@ 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/darvilab/Training%20Sentence%20Translation/runs/b7p9pw9o)
+[<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/darvilab/Training%20Sentence%20Translation/runs/nul533k2)
 # mbart-en-np-seqtoseq-sentence-translation
 
 This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9597
-- Bleu: 48.1358
-- Gen Len: 9.3
+- Loss: 1.1896
+- Bleu: 40.4595
+- Gen Len: 10.288
 
 ## Model description
 
@@ -39,8 +39,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- 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
@@ -50,11 +50,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
-| 2.9421        | 1.0   | 7    | 1.7883          | 10.4307 | 9.1     |
-| 1.5462        | 2.0   | 14   | 1.3980          | 7.5693  | 7.5     |
-| 1.0467        | 3.0   | 21   | 0.9333          | 45.1288 | 9.4     |
-| 0.4864        | 4.0   | 28   | 0.9698          | 48.1358 | 9.3     |
-| 0.4757        | 5.0   | 35   | 0.9597          | 48.1358 | 9.3     |
+| 1.0147        | 1.0   | 1250 | 0.9876          | 40.1501 | 9.885   |
+| 0.6038        | 2.0   | 2500 | 1.0122          | 40.728  | 10.113  |
+| 0.3557        | 3.0   | 3750 | 1.0809          | 35.9297 | 10.844  |
+| 0.2071        | 4.0   | 5000 | 1.1502          | 40.4318 | 10.28   |
+| 0.1241        | 5.0   | 6250 | 1.1896          | 40.4595 | 10.288  |
 
 
 ### Framework versions