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brendaogutu
/
mul-sw-en-translation-phase2

Translation
TensorBoard
Safetensors
Swahili
English
marian
swahili
english
opus-mt
openchs
Model card Files
xet
 Metrics Community
brendaogutu commited on
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e48d5e5
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1 Parent(s): ce9f2c6

Upload fine-tuned model - BLEU: 0.1289

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1
+ ---
2
+ language:
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+ - sw
4
+ - en
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+ license: apache-2.0
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+ tags:
7
+ - translation
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+ - swahili
9
+ - english
10
+ - opus-mt
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+ - openchs
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+ datasets:
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+ - nllb
14
+ - ccaligned
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+ metrics:
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+ - bleu
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+ - chrf
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+ - comet
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+ ---
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+
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+ # Swahili-English Translation Model for Child Helpline Services
22
+
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+ ## Model Description
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+
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+ This model is a fine-tuned version of `brendaogutu/mul-sw-en-translation-phase1` for Swahili-to-English translation, specifically optimized for child helpline call transcriptions in East Africa.
26
+
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+ **Developed by:** BITZ IT Consulting Ltd
28
+ **Project:** OpenCHS (Open Child Helpline System)
29
+ **Funded by:** UNICEF Venture Fund
30
+ **License:** Apache 2.0
31
+
32
+ ## Performance
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+
34
+ ### Test Set (General Translation)
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+ - **BLEU:** 0.1289
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+ - **chrF:** 32.25
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+ - **Improvement over baseline:** +0.0%
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+
39
+ ### Domain Evaluation (Call Transcriptions)
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+ - **Domain BLEU:** 0.0000
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+ - **Domain chrF:** 1.18
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+ - **Domain COMET-QE:** 0.0000
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+
44
+ ## Intended Use
45
+
46
+ **Primary Use Case:** Translating Swahili helpline call transcriptions to English for case documentation, quality assurance, and cross-border referrals.
47
+
48
+ **Languages:** Swahili (source) → English (target)
49
+
50
+ ## Usage
51
+
52
+ ```python
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+ from transformers import MarianTokenizer, MarianMTModel
54
+
55
+ model_name = "brendaogutu/mul-sw-en-translation-phase2"
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+ tokenizer = MarianTokenizer.from_pretrained(model_name)
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+ model = MarianMTModel.from_pretrained(model_name)
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+
59
+ swahili_text = "Habari za asubuhi. Ninaitwa Amina na nina miaka 14."
60
+ inputs = tokenizer(swahili_text, return_tensors="pt", padding=True)
61
+ outputs = model.generate(**inputs, num_beams=5, max_length=256)
62
+ translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
63
+ print(translation)
64
+ ```
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+
66
+ ## Training Details
67
+
68
+ **Base Model:** brendaogutu/mul-sw-en-translation-phase1
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+ **Training Epochs:** 6
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+ **Batch Size:** 256
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+ **Learning Rate:** 2e-05
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+ **Hardware:** NVIDIA GPU with FP16 mixed precision
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+
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+ ---
75
+
76
+ *This model is part of the OpenCHS project supporting child helpline services across East Africa.*
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