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README.md

@@ -1,27 +1,24 @@
 ---
 tags:
 - adapter-transformers
+- adapterhub:am/wikipedia-amharic-20240320
 - xlm-roberta
-- adapterhub:am/wikipedia-amharic-20240320"
 datasets:
 - wikipedia
-pipeline_tag: fill-mask
-language:
-- am
 ---
 
-# Adapter `solwol/xml-roberta-amharic` for xlm-roberta-base
+# Adapter `solwol/xml-roberta-base-adapter-amharic` for xlm-roberta-base
 
-An [adapter](https://adapterhub.ml) for the `xlm-roberta-base` model that was trained on the [fill-mask/wikipedia-amharic](https://adapterhub.ml/explore/fill-mask/wikipedia-amharic/) dataset and includes a prediction head for masked lm.
+An [adapter](https://adapterhub.ml) for the `xlm-roberta-base` model that was trained on the [am/wikipedia-amharic-20240320](https://adapterhub.ml/explore/am/wikipedia-amharic-20240320/) dataset and includes a prediction head for masked lm.
 
 This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.
 
 ## Usage
 
-First, install `transformers`, `adapters`:
+First, install `adapters`:
 
 ```
-pip install -U transformers adapters 
+pip install -U adapters
 ```
 
 Now, the adapter can be loaded and activated like this:
@@ -32,43 +29,15 @@ from adapters import AutoAdapterModel
 model = AutoAdapterModel.from_pretrained("xlm-roberta-base")
 adapter_name = model.load_adapter("solwol/xml-roberta-base-adapter-amharic", source="hf", set_active=True)
 ```
-Next, to perform fill mask tasks:
 
-```python
+## Architecture & Training
 
-from transformers import AutoTokenizer, FillMaskPipeline
+<!-- Add some description here -->
 
-tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base")
-fillmask = FillMaskPipeline(model=model, tokenizer=tokenizer)
+## Evaluation results
 
-inputs = ["መልካም አዲስ <mask> ይሁን",
-         "የኢትዮጵያ ዋና <mask> አዲስ አበባ ነው",
-         "ኬንያ የ ኢትዮጵያ አዋሳኝ <mask> አንዷ ናት",
-         "አጼ ምኒሊክ የኢትዮጵያ <mask> ነበሩ"]
+<!-- Add some description here -->
 
-outputs = fillmask(inputs)
-outputs[0]
+## Citation
 
-[{'score': 0.31237369775772095,
-  'token': 17733,
-  'token_str': 'ቀን',
-  'sequence': 'መልካም አዲስ ቀን ይሁን'},
- {'score': 0.17704728245735168,
-  'token': 19202,
-  'token_str': 'አበባ',
-  'sequence': 'መልካም አዲስ አበባ ይሁን'},
- {'score': 0.17629213631153107,
-  'token': 98040,
-  'token_str': 'አመት',
-  'sequence': 'መልካም አዲስ አመት ይሁን'},
- {'score': 0.08915291726589203,
-  'token': 25186,
-  'token_str': 'ዓመት',
-  'sequence': 'መልካም አዲስ ዓመት ይሁን'},
- {'score': 0.060819510370492935,
-  'token': 118502,
-  'token_str': 'ሳምንት',
-  'sequence': 'መልካም አዲስ ሳምንት ይሁን'}]
-```
-## Fine-tuning data
-Used some of wikipedia's amharic dataset; snapshot date="20240320"
+<!-- Add some description here -->

pytorch_adapter.bin

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pytorch_model_head.bin

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