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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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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: bert-finetuned-ner |
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results: [] |
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language: |
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- en |
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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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# bert-finetuned-AAVE-PoS |
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This model is a version of [bert-base-cased](https://huggingface.co/bert-base-cased) fine-tuned on a [dataset](https://bitbucket.org/soegaard/aave-pos16/src/master/data) of African American Vernacular English (AAVE) which was published alongside [Jørgensen et al. 2016](https://aclanthology.org/N16-1130.pdf). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2582 |
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- Precision: 0.8632 |
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- Recall: 0.8730 |
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- F1: 0.8681 |
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- Accuracy: 0.9356 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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This model is intended to help close the gap in part-of-speech tagging performance between Standard American English (SAE) and African American English (AAVE) which differ liguistically in many [well-documented](http://www.johnrickford.com/portals/45/documents/papers/Rickford-1999e-Phonological-and-Grammatical-Features-of-AAVE.pdf) ways. It was fine-tuned on data gathered from Twitter, and is thus ingrained with what linguists call 'register bias'. |
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## Training and evaluation data |
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Code hosted at [GitHub](https://github.com/DrewGalbraith/AAE-PoS/tree/main). |
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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: 3 (this amount of data overfits on 3+) |
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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 | 223 | 0.2982 | 0.8196 | 0.8350 | 0.8272 | 0.9216 | |
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| No log | 2.0 | 446 | 0.2625 | 0.8599 | 0.8680 | 0.8640 | 0.9326 | |
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| 0.4647 | 3.0 | 669 | 0.2582 | 0.8632 | 0.8730 | 0.8681 | 0.9356 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.13.1+cpu |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
