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finetuning-sentiment-model-1000-samples – AI Model by klorine28 | AlphaNeural AI
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finetuning-sentiment-model-1000-samples
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
finiteautomata/bertweet-base-sentiment-analysis
finetune
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model-1000-samples
This model is a fine-tuned version of
finiteautomata/bertweet-base-sentiment-analysis
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0307
Accuracy: 0.9962
F1: 0.9965
Recall: 1.0
Precision: 0.9931
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Framework versions
Transformers 4.39.3
Pytorch 1.13.1+cpu
Datasets 2.18.0
Tokenizers 0.15.2
