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README.md
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This model was finetuned and evaluated on the following amharic nlp tasks
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- Sentiment Classification
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###
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The
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dataset to classify the given text as having `positive` or `negative` sentiment
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|Model|Size (# params)|
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|bert-small-amharic|27.8M|
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|bert-mini-amharic|10.7M|
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|bert-tiny-amharic|4.18M|
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|xlm-roberta-base|279M
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|am-roberta|443M
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### Named Entity Recognition
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The model was finetuned on the [amharic-named-entity-recognition](https://huggingface.co/datasets/rasyosef/amharic-named-entity-recognition) dataset.
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|Model|Size (# params)| Precision | Recall | F1 |
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| --- | ------------- | --------- |------- | -- |
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|bert-medium-amharic|40.5M|0.64|0.73|0.68|
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|bert-small-amharic|27.8M|0.64|0.72|0.68|
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|bert-mini-amharic|10.7M|0.60|0.67|0.64|
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|bert-tiny-amharic|4.18M|0.50|0.59|0.54|
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|xlm-roberta-base|279M|0.69|0.79|0.73|
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|am-roberta|443M|0.67|0.72|0.69|
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This model was finetuned and evaluated on the following amharic nlp tasks
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- Sentiment Classification
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- Dataset: [amharic-sentiment](https://huggingface.co/datasets/rasyosef/amharic-sentiment)
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- Named Entity Recognition
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- Dataset: [amharic-named-entity-recognition](https://huggingface.co/datasets/rasyosef/amharic-named-entity-recognition)
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### Finetuned Model Performance
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The reported F1 scores are macro averages.
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|Model|Size (# params)| Perplexity|Sentiment (F1)| Named Entity Recognition (F1)|
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|-----|---------------|-----------|--------------|------------------------------|
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|**bert-medium-amharic**|**40.5M**|**13.74**|**0.83**|**0.68**|
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|bert-small-amharic|27.8M|15.96|0.83|0.68|
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|bert-mini-amharic|10.7M|22.42|0.81|0.64|
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|bert-tiny-amharic|4.18M|71.52|0.79|0.54|
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|xlm-roberta-base|279M||0.83|0.73|
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|am-roberta|443M||0.82|0.69|
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