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README.md

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+Hugging Face's logo
+---
+language: am
+datasets:
+
+---
+# bert-base-multilingual-cased-finetuned-amharic
+## Model description
+**bert-base-multilingual-cased-finetuned-amharic** is a **Amharic BERT** model obtained by replacing mBERT vocabulary by amharic vocabulary because the language was not supported, and fine-tuning **bert-base-multilingual-cased** model on Amharic language texts.  It provides **better performance** than the multilingual Amharic on named entity recognition datasets.  
+
+Specifically, this model is a *bert-base-multilingual-cased* model that was fine-tuned on Amharic corpus using Amharic vocabulary. 
+## Intended uses & limitations
+#### How to use
+You can use this model with Transformers *pipeline* for masked token prediction.
+```python
+>>> from transformers import pipeline
+>>> unmasker = pipeline('fill-mask', model='Davlan/bert-base-multilingual-cased-finetuned-amharic')
+>>> unmasker("የአሜሪካ የአፍሪካ ቀንድ ልዩ መልዕክተኛ ጄፈሪ ፌልትማን በአራት አገራት የሚያደጉትን [MASK] መጀመራቸውን የአሜሪካ የውጪ ጉዳይ ሚንስቴር አስታወቀ።")
+                    
+
+```
+#### Limitations and bias
+This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains. 
+## Training data
+This model was fine-tuned on [Amharic CC-100](http://data.statmt.org/cc-100/)
+
+## Training procedure
+This model was trained on a single NVIDIA V100 GPU
+
+## Eval results on Test set (F-score, average over 5 runs)
+Dataset| mBERT F1 | am_bert F1
+-|-|-
+[MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 0.0 | 60.89
+
+### BibTeX entry and citation info
+By David Adelani
+```
+
+```
+
+