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Sentiment-review-analysis-roberta-3 – AI Model by gyesibiney | AlphaNeural AI
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Sentiment-review-analysis-roberta-3
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transformers
pytorch
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Roberta-capstone_2
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3485
Accuracy: 0.9400
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
0.2568
1.0
623
0.1971
0.9265
0.1581
2.0
1246
0.2102
0.9339
0.109
3.0
1869
0.3126
0.9356
0.0687
4.0
2492
0.3040
0.9382
0.0199
5.0
3115
0.3485
0.9400
Framework versions
Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
