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news-sentiment-analysis-roberta – AI Model by rahilv | AlphaNeural AI
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news-sentiment-analysis-roberta
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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news-sentiment-roberta
This model is a fine-tuned version of
FacebookAI/roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4288
Accuracy: 0.8300
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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4993
1.0
1275
0.4332
0.8307
0.3524
2.0
2550
0.4369
0.8356
0.2584
3.0
3825
0.4830
0.8393
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3
