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README.md
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---
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license:
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tags:
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- generated_from_trainer
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datasets:
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-
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: khmer-pos-roberta-10
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results:
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- name: Accuracy
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type: accuracy
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value: 0.9735370853522176
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.1063
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- Precision: 0.9512
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- seanghay/khPOS
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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widget:
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- text: គាត់ផឹកទឹកនៅភ្នំពេញ
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- text: តើលោកស្រីបានសាកសួរទៅគាត់ទេ?
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- text: នេត្រា មិនដឹងសោះថាអ្នកជាមនុស្ស!
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model-index:
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- name: khmer-pos-roberta-10
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results:
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- name: Accuracy
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type: accuracy
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value: 0.9735370853522176
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language:
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- km
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library_name: transformers
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pipeline_tag: token-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Khmer Part of Speech Tagging with XLM RoBERTa
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [khPOS](https://huggingface.co/seanghay/khPOS) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1063
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- Precision: 0.9512
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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