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--- |
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license: afl-3.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lg-ner |
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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: luganda-ner-v5 |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: lg-ner |
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type: lg-ner |
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config: lug |
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split: test |
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args: lug |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8502710027100271 |
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- name: Recall |
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type: recall |
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value: 0.8428475486903962 |
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- name: F1 |
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type: f1 |
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value: 0.8465430016863407 |
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- name: Accuracy |
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type: accuracy |
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value: 0.959089589080877 |
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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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# luganda-ner-v5 |
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This model is a fine-tuned version of [masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0](https://huggingface.co/masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0) on the lg-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2328 |
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- Precision: 0.8503 |
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- Recall: 0.8428 |
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- F1: 0.8465 |
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- Accuracy: 0.9591 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 261 | 0.2276 | 0.7703 | 0.6441 | 0.7015 | 0.9353 | |
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| 0.3176 | 2.0 | 522 | 0.1848 | 0.8431 | 0.7542 | 0.7962 | 0.9545 | |
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| 0.3176 | 3.0 | 783 | 0.1871 | 0.8564 | 0.8173 | 0.8364 | 0.9576 | |
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| 0.0753 | 4.0 | 1044 | 0.2015 | 0.8691 | 0.8294 | 0.8488 | 0.9614 | |
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| 0.0753 | 5.0 | 1305 | 0.2325 | 0.8616 | 0.8361 | 0.8487 | 0.9584 | |
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| 0.0261 | 6.0 | 1566 | 0.2328 | 0.8503 | 0.8428 | 0.8465 | 0.9591 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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