allmalab
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bert-small-aze

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bert-small-aze

This model is a trained version of prajjwal1/bert-small architecture on the allmalab/DOLLMA dataset.

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: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10000
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.37.1
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1

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Safetensors

Model size

46M params

Tensor type

F32

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Finetuned from

Evaluation results

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