End of training

README.md

@@ -1,82 +1,77 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: Helsinki-NLP/opus-mt-vi-en
-tags:
-- translation
-- generated_from_trainer
-metrics:
-- bleu
-model-index:
-- name: tatoeba-vi-tok
-  results: []
-datasets:
-- NetherQuartz/tatoeba-tokipona
-language:
-- vi
-- tok
----
-
-<!-- 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. -->
-
-# tatoeba-vi-tok
-
-This model is a fine-tuned version of [Helsinki-NLP/opus-mt-vi-en](https://huggingface.co/Helsinki-NLP/opus-mt-vi-en) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5992
-- Bleu: 51.0628
-
-## 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: 64
-- eval_batch_size: 64
-- seed: 42
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- num_epochs: 15
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step  | Validation Loss | Bleu    |
-|:-------------:|:-----:|:-----:|:---------------:|:-------:|
-| 1.1834        | 1.0   | 1191  | 0.9327          | 38.0949 |
-| 0.9011        | 2.0   | 2382  | 0.7766          | 43.8510 |
-| 0.757         | 3.0   | 3573  | 0.7090          | 46.2681 |
-| 0.6945        | 4.0   | 4764  | 0.6740          | 47.6159 |
-| 0.6477        | 5.0   | 5955  | 0.6508          | 48.2589 |
-| 0.6069        | 6.0   | 7146  | 0.6340          | 49.0915 |
-| 0.5792        | 7.0   | 8337  | 0.6245          | 49.5996 |
-| 0.5547        | 8.0   | 9528  | 0.6158          | 49.9003 |
-| 0.5333        | 9.0   | 10719 | 0.6104          | 50.2630 |
-| 0.5204        | 10.0  | 11910 | 0.6067          | 50.6028 |
-| 0.5086        | 11.0  | 13101 | 0.6028          | 50.8309 |
-| 0.4949        | 12.0  | 14292 | 0.6014          | 50.9340 |
-| 0.4868        | 13.0  | 15483 | 0.6005          | 50.9385 |
-| 0.4792        | 14.0  | 16674 | 0.5992          | 51.0628 |
-| 0.4781        | 15.0  | 17865 | 0.5994          | 51.1826 |
-
-
-### Framework versions
-
-- Transformers 4.52.4
-- Pytorch 2.7.1+cu128
-- Datasets 3.6.0
-- Tokenizers 0.21.1
+---
+library_name: transformers
+license: apache-2.0
+base_model: Helsinki-NLP/opus-mt-vi-en
+tags:
+- translation
+- generated_from_trainer
+metrics:
+- bleu
+model-index:
+- name: tatoeba-vi-tok
+  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. -->
+
+# tatoeba-vi-tok
+
+This model is a fine-tuned version of [Helsinki-NLP/opus-mt-vi-en](https://huggingface.co/Helsinki-NLP/opus-mt-vi-en) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6910
+- Bleu: 46.4356
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu    |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 1.2609        | 1.0   | 1167  | 1.0286          | 33.8552 |
+| 0.98          | 2.0   | 2334  | 0.8700          | 39.5255 |
+| 0.8347        | 3.0   | 3501  | 0.8036          | 41.4872 |
+| 0.7753        | 4.0   | 4668  | 0.7661          | 43.3025 |
+| 0.7272        | 5.0   | 5835  | 0.7389          | 44.2770 |
+| 0.6876        | 6.0   | 7002  | 0.7254          | 45.1330 |
+| 0.659         | 7.0   | 8169  | 0.7153          | 45.4847 |
+| 0.6383        | 8.0   | 9336  | 0.7067          | 45.4353 |
+| 0.6122        | 9.0   | 10503 | 0.7015          | 45.7612 |
+| 0.5998        | 10.0  | 11670 | 0.6979          | 46.0799 |
+| 0.5836        | 11.0  | 12837 | 0.6960          | 46.1173 |
+| 0.5732        | 12.0  | 14004 | 0.6928          | 46.2538 |
+| 0.5607        | 13.0  | 15171 | 0.6919          | 46.3801 |
+| 0.553         | 14.0  | 16338 | 0.6911          | 46.3629 |
+| 0.5518        | 15.0  | 17505 | 0.6910          | 46.4356 |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.7.1+cu128
+- Datasets 3.6.0
+- Tokenizers 0.21.1

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