NLP_Capstone – AI Model by petermutwiri | AlphaNeural AI

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petermutwiri/
NLP_Capstone

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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NLP_Capstone

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

Loss: 0.2591
Accuracy: 0.9143

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: 5e-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	Accuracy
0.4283	0.2	500	0.3811	0.8715
0.397	0.4	1000	0.4590	0.8601
0.3813	0.6	1500	0.2912	0.9103
0.3309	0.8	2000	0.2591	0.9143
0.3138	1.0	2500	0.3744	0.9060
0.2552	1.2	3000	0.2948	0.9070
0.2317	1.41	3500	0.3014	0.8914
0.2592	1.61	4000	0.3275	0.9187
0.2754	1.81	4500	0.3449	0.9133
0.242	2.01	5000	0.3925	0.9085
0.1777	2.21	5500	0.3589	0.9213
0.1797	2.41	6000	0.4360	0.9125
0.1775	2.61	6500	0.3475	0.9257
0.1731	2.81	7000	0.3797	0.9249
0.1705	3.01	7500	0.3802	0.9211
0.1271	3.21	8000	0.3827	0.9273
0.1071	3.41	8500	0.3927	0.9281
0.0958	3.61	9000	0.4263	0.9275
0.1123	3.81	9500	0.3773	0.9273
0.0802	4.01	10000	0.4282	0.9293
0.0521	4.22	10500	0.4677	0.9247
0.063	4.42	11000	0.4233	0.9267
0.069	4.62	11500	0.4097	0.9293
0.0367	4.82	12000	0.4336	0.9283

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1