MinhKemm
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results

Text Classification

Generated from Trainer

text-embeddings-inference

Model card Files Files and versions

results

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.4003
eval_accuracy: 0.8358
eval_f1: 0.8893
eval_runtime: 62.7183
eval_samples_per_second: 6.505
eval_steps_per_second: 0.415
epoch: 0.8696
step: 200

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: 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

Framework versions

Transformers 4.55.4
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4

Downloads last month: 2

Safetensors

Model size

0.1B params

Tensor type

F32

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