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frankwong2001/distilbert-imdb-tiny-cpu

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face
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Model Card

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distilbert-imdb-tiny-cpu

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

  • —Loss: 0.3821

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 1

Training results

Training LossEpochStepValidation Loss
0.59921.0630.3821

Framework versions

  • —Transformers 5.8.0
  • —Pytorch 2.11.0+cu130
  • —Datasets 4.8.5
  • —Tokenizers 0.22.2

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Generated by ML Intern

This model repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.

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  • —Source code: https://github.com/huggingface/ml-intern

Usage

python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = 'frankwong2001/distilbert-imdb-tiny-cpu'
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

For non-causal architectures, replace AutoModelForCausalLM with the appropriate AutoModel class.