xlmr-base-finetuned-hausa-2e-4 – AI Model by grace-pro | AlphaNeural AI

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grace-pro/
xlmr-base-finetuned-hausa-2e-4

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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xlmr-base-finetuned-hausa-2e-4

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2708
Precision: 0.1719
Recall: 0.0235
F1: 0.0414
Accuracy: 0.9247

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: 0.0002
train_batch_size: 16
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
0.2716	1.0	1312	0.2690	0.1719	0.0235	0.0414	0.9247
0.2744	2.0	2624	0.2697	0.1719	0.0235	0.0414	0.9247
0.2735	3.0	3936	0.2693	0.1719	0.0235	0.0414	0.9247
0.2739	4.0	5248	0.2697	0.1719	0.0235	0.0414	0.9247
0.2709	5.0	6560	0.2708	0.1719	0.0235	0.0414	0.9247

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3