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bert-sst2-sentiment-lora – AI Model by asm3515 | AlphaNeural AI
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asm3515
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bert-sst2-sentiment-lora
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peft
safetensors
generated_from_trainer
google-bert/bert-base-uncased
adapter
apache-2.0
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bert-sst2-sentiment-lora
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: 0.2664
Accuracy: 0.9094
F1: 0.9123
Precision: 0.8993
Recall: 0.9257
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
0.3043
1.0
4210
0.2483
0.9128
0.9148
0.9107
0.9189
0.2494
2.0
8420
0.2577
0.9083
0.9109
0.9009
0.9212
0.1861
3.0
12630
0.2664
0.9094
0.9123
0.8993
0.9257
Framework versions
PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1
