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afriberta-finetuned-hausa – AI Model by grace-pro | AlphaNeural AI
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afriberta-finetuned-hausa
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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afriberta-finetuned-hausa
This model is a fine-tuned version of
castorini/afriberta_large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1242
Precision: 0.7104
Recall: 0.5095
F1: 0.5934
Accuracy: 0.9647
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1369
1.0
2624
0.1256
0.6856
0.4541
0.5463
0.9614
0.1103
2.0
5248
0.1195
0.7014
0.4947
0.5802
0.9637
0.0868
3.0
7872
0.1242
0.7104
0.5095
0.5934
0.9647
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
