metadata

language:
  - en
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: imdb_distilbert-base-uncased
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: imdb
          type: imdb
          config: plain_text
          split: test
          args: imdb
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.87736

imdb_distilbert-base-uncased

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

Loss: 0.2911
Accuracy: 0.8774

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6487	0.2	78	0.4402	0.8117
0.402	0.4	156	0.3563	0.8416
0.3528	0.6	234	0.3522	0.8434
0.3362	0.8	312	0.3099	0.8652
0.3184	1.0	390	0.3028	0.8700
0.265	1.2	468	0.3052	0.8738
0.2593	1.4	546	0.2983	0.8735
0.2537	1.6	624	0.2977	0.8754
0.2558	1.8	702	0.2911	0.8774
0.2476	1.99	780	0.2907	0.8751
0.1941	2.19	858	0.3151	0.8774
0.1873	2.39	936	0.3104	0.8764
0.1869	2.59	1014	0.3181	0.8771
0.1807	2.79	1092	0.3148	0.8764
0.1967	2.99	1170	0.3141	0.8766

Framework versions

Transformers 4.35.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1