Update README.md

README.md

@@ -6,7 +6,7 @@ language:
 metrics:
 - bleu
 base_model:
-- Helsinki-NLP/opus-mt-en-hi
+- Helsinki-NLP/opus-mt-en-zh
 pipeline_tag: translation
 tags:
 - nmt
@@ -16,9 +16,9 @@ library_name: transformers
 ---
 # Model Card for Model ID
 
-The `eng_tag_nmt` model is a neural machine translation (NMT) model fine-tuned on the `GinLish Corpus v0.1.0` (under development), which consists of `English` and `Tagin` language pairs. Tagin, an `extremely low-resource language` spoken in Arunachal Pradesh, India, faces challenges due to a scarcity of digital resources and linguistic datasets. The goal of this model is to provide translation support for Tagin, helping to preserve and promote its use in digital spaces.
+The `eng-tagin-nmt` model is a neural machine translation (NMT) model fine-tuned on the `GinLish Corpus v0.1.0` (under development), which consists of `English` and `Tagin` language pairs. Tagin, an `extremely low-resource language` spoken in Arunachal Pradesh, India, faces challenges due to a scarcity of digital resources and linguistic datasets. The goal of this model is to provide translation support for Tagin, helping to preserve and promote its use in digital spaces.
 
-To develop `eng_tag_nmt`, the pre-trained model `Helsinki-NLP/opus-mt-en-hi` (English-to-Hindi) was leveraged as a foundation, given the structural similarities between Hindi and Tagin in a multilingual context. Transfer learning on this model allowed efficient adaptation of the Tagin translation model, despite limited language data.
+To develop `eng-tagin-nmt`, the pre-trained model `Helsinki-NLP/opus-mt-en-hi` (English-to-Hindi) was leveraged as a foundation, given the structural similarities between Hindi and Tagin in a multilingual context. Transfer learning on this model allowed efficient adaptation of the Tagin translation model, despite limited language data.
 
 ## Model Details
 
@@ -29,7 +29,7 @@ To develop `eng_tag_nmt`, the pre-trained model `Helsinki-NLP/opus-mt-en-hi` (En
 - **Email:** [[email protected]](mailto:[email protected]) or [[email protected]](mailto:[email protected])
 - **Model type:** Translation
 - **Language(s) (NLP):** English (en) and Tagin (tag)
-- **Finetuned from model:** Helsinki-NLP/opus-mt-en-hi
+- **Finetuned from model:** Helsinki-NLP/opus-mt-en-zh
 
 
 ## Uses
@@ -62,11 +62,11 @@ The model achieved the following metrics after 10 training epochs:
 
 | Metric                | Value             |
 |----------------------|-------------------|
-| BLEU Score           | 26.2526            |
-| Evaluation Runtime    | 628.34 seconds    |
+| BLEU Score           | 27.9589        |
+| Evaluation Runtime    | 670.2117 seconds    |
 
 The model’s BLEU score suggests promising results, with the low evaluation loss indicating strong translation performance on the GinLish Corpus, suitable for practical applications. This model represents a significant advancement for Tagin language resources, enabling English-to-Tagin translation in NLP applications.
 
 #### Summary
 
-The `eng_tag_nmt` model is currently in its early phase of development. To enhance its performance, it requires a more substantial dataset and improved training resources. This would facilitate better generalization and accuracy in translating between English and Tagin, addressing the challenges faced by this extremely low-resource language. As the model evolves, ongoing efforts will be necessary to refine its capabilities further.
+The `eng-tagin-nmt` model is currently in its early phase of development. To enhance its performance, it requires a more substantial dataset and improved training resources. This would facilitate better generalization and accuracy in translating between English and Tagin, addressing the challenges faced by this extremely low-resource language. As the model evolves, ongoing efforts will be necessary to refine its capabilities further.