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results – AI Model by mrwolf883 | AlphaNeural AI
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transformers
safetensors
bert
text-classification
generated_from_trainer
UBC-NLP/MARBERT
finetune
text-embeddings-inference
endpoints_compatible
us
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This model is a fine-tuned version of
UBC-NLP/MARBERT
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3539
Accuracy: 0.8538
F1: 0.7298
Precision: 0.8739
Recall: 0.6265
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
No log
1.0
307
0.3549
0.8441
0.6974
0.8552
0.5888
0.3472
2.0
614
0.4719
0.8612
0.7801
0.7551
0.8069
0.3472
3.0
921
0.5533
0.8612
0.7675
0.7850
0.7508
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2