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tiny-bert-sst2-distilled_original

Text Classification

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text-embeddings-inference

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tiny-bert-sst2-distilled_original

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:

eval_loss: 1.8486
eval_accuracy: 0.7936
eval_runtime: 2.677
eval_samples_per_second: 325.739
eval_steps_per_second: 2.615
epoch: 1.0
step: 527

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: 0.00023791117612513647
train_batch_size: 128
eval_batch_size: 128
seed: 33
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

Downloads last month: 3

Safetensors

Model size

4.39M params

Tensor type

F32

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Model tree for jysh1023/tiny-bert-sst2-distilled_original

Base model

google/bert_uncased_L-2_H-128_A-2

Finetuned

(63)

this model

Dataset used to train jysh1023/tiny-bert-sst2-distilled_original