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bert-sst2-sentiment-full – AI Model by asm3515 | AlphaNeural AI
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asm3515
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bert-sst2-sentiment-full
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transformers
safetensors
roberta
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-sst2-sentiment-full
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3013
Accuracy: 0.9197
F1: 0.9201
Precision: 0.9329
Recall: 0.9077
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: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.1068
1.0
4210
0.2625
0.9128
0.9116
0.9423
0.8829
0.1025
2.0
8420
0.3288
0.9094
0.9133
0.8908
0.9369
0.0646
3.0
12630
0.3013
0.9197
0.9201
0.9329
0.9077
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1
