metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - stanfordnlp/imdb
metrics:
  - perplexity
model-index:
  - name: test-distilbert-base-uncased-finetuned-imdb
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: imdb
          type: kde4
          args: fill-mask
        metrics:
          - name: perplexity
            type: perplexity
            value: 12.05
pipeline_tag: fill-mask

distilbert-base-uncased-finetuned-imdb

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

Loss: 2.4894

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.6819	1.0	157	2.4978
2.5872	2.0	314	2.4488
2.527	3.0	471	2.4823

Framework versions

Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1