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digidawfinal2 – AI Model by bwahyuh | AlphaNeural AI
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digidawfinal2
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
intfloat/multilingual-e5-small
finetune
mit
autotrain_compatible
endpoints_compatible
us
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digidawfinal2
This model is a fine-tuned version of
intfloat/multilingual-e5-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6325
Accuracy: 0.826
Precision: 0.4849
Recall: 0.3920
F1: 0.4038
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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
1.3648
1.0
157
0.7544
0.8
0.1481
0.1495
0.1451
1.0523
2.0
314
0.7241
0.791
0.3328
0.3616
0.3064
0.8635
3.0
471
0.6325
0.826
0.4849
0.3920
0.4038
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
