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afriberta-base-finetuned-igbo
grace-pro/afriberta-base-finetuned-igbo
afriberta-base-finetuned-igbo is a token classification model from grace-pro. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jul 11, 2023
- Updated
- Jul 11, 2023
- SHA
- eb0c24b2
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
afriberta-base-finetuned-igbo
This model is a fine-tuned version of castorini/afriberta_base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2159
- Precision: 0.7242
- Recall: 0.5039
- F1: 0.5943
- Accuracy: 0.9367
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1989 | 1.0 | 2514 | 0.2020 | 0.7134 | 0.4098 | 0.5206 | 0.9285 |
| 0.1759 | 2.0 | 5028 | 0.2125 | 0.7383 | 0.4263 | 0.5405 | 0.9315 |
| 0.1417 | 3.0 | 7542 | 0.2044 | 0.7320 | 0.4736 | 0.5751 | 0.9352 |
| 0.1279 | 4.0 | 10056 | 0.2066 | 0.7341 | 0.4884 | 0.5866 | 0.9363 |
| 0.1132 | 5.0 | 12570 | 0.2159 | 0.7242 | 0.5039 | 0.5943 | 0.9367 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jul 11, 2023
- Updated
- Jul 11, 2023