sentiment_analysis – AI Model by IsaacSarps | AlphaNeural AI

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IsaacSarps/
sentiment_analysis

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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sentiment_analysis

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

Loss: 0.8114
F1 Score: 0.7322

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Score
0.7577	1.0	1000	0.7996	0.6603
0.7168	2.0	2000	0.7362	0.6627
0.7201	3.0	3000	0.7231	0.6675
0.6752	4.0	4000	0.7051	0.6970
0.6374	5.0	5000	0.7167	0.7007
0.6288	6.0	6000	0.7278	0.7193
0.5579	7.0	7000	0.8242	0.7190
0.5485	8.0	8000	0.7587	0.7291
0.5309	9.0	9000	0.7876	0.7269
0.4767	10.0	10000	0.8114	0.7322

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3