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bert-qlora-imdb-sentiment-finetuned – AI Model by shravankasagoni | AlphaNeural AI
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shravankasagoni
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bert-qlora-imdb-sentiment-finetuned
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peft
safetensors
generated_from_trainer
dipanjanS/imdb_sentiment_finetune_dataset20k
google-bert/bert-base-uncased
adapter
apache-2.0
us
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bert-qlora-imdb-sentiment-finetuned
This model is a fine-tuned version of
bert-base-uncased
on dataset
imdb_sentiment_finetune_dataset20k
.
It achieves the following results on the evaluation set:
Loss: 0.4501
Accuracy: 0.7918
F1: 0.7918
Precision: 0.7919
Recall: 0.7918
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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.4668
1.0
500
0.4675
0.7793
0.7793
0.7800
0.7793
0.4639
2.0
1000
0.4814
0.7763
0.7747
0.7883
0.7763
0.4537
3.0
1500
0.4501
0.7918
0.7918
0.7919
0.7918
Framework versions
PEFT 0.15.2
Transformers 4.52.4
Pytorch 2.8.0.dev20250319+cu128
Datasets 3.6.0
Tokenizers 0.21.1
