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finetuned-Sentiment-classfication-ROBERTA-model – AI Model by slickdata | AlphaNeural AI
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finetuned-Sentiment-classfication-ROBERTA-model
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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finetuned-Sentiment-classfication-ROBERTA-model
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2222
Rmse: 0.2936
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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 16
Training results
Training Loss
Epoch
Step
Validation Loss
Rmse
0.6684
2.72
500
0.3931
0.4892
0.1963
5.43
1000
0.2222
0.2936
0.0755
8.15
1500
0.2479
0.2757
0.0413
10.86
2000
0.3233
0.2794
0.0213
13.58
2500
0.3590
0.2689
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
