my_model – AI Model by onsba | AlphaNeural AI

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my_model

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distilbert/distilbert-base-uncased

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my_model

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 5.9953
Start Accuracy: 0.5270
End Accuracy: 0.5270
Overall Accuracy: 0.5270
Start Precision: 0.2548
End Precision: 0.2696
Start Recall: 0.2307
End Recall: 0.2805
Start F1 Score: 0.2338
End F1 Score: 0.2644

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: 1e-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	Start Accuracy	End Accuracy	Overall Accuracy	Start Precision	End Precision	Start Recall	End Recall	Start F1 Score	End F1 Score
0.0302	1.0	22	6.1169	0.5405	0.4865	0.5135	0.2951	0.2569	0.2669	0.2371	0.2732	0.2331
0.0331	2.0	44	6.1384	0.4730	0.4730	0.4730	0.2056	0.2529	0.1692	0.2470	0.1801	0.2376
0.0332	3.0	66	6.0663	0.5135	0.5135	0.5135	0.2168	0.2434	0.1975	0.2619	0.1974	0.2446
0.0341	4.0	88	6.0363	0.5270	0.5270	0.5270	0.2548	0.2696	0.2307	0.2805	0.2338	0.2644
0.0213	5.0	110	5.9953	0.5270	0.5270	0.5270	0.2548	0.2696	0.2307	0.2805	0.2338	0.2644

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2