README.md

metadata

license: openrail
base_model: versae/gzip-bert
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: gzipbert_imdb_rpe_250k_v4
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: imdb
          type: imdb
          config: plain_text
          split: test
          args: plain_text
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.49512

gzipbert_imdb_rpe_250k_v4

This model is a fine-tuned version of versae/gzip-bert on the imdb dataset. It achieves the following results on the evaluation set:

• Loss: 3.4034
• Accuracy: 0.4951

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: 1e-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0425	1.0	1563	2.5908	0.5231
0.0357	2.0	3126	2.8405	0.5343
0.0291	3.0	4689	2.8759	0.5562
0.0313	4.0	6252	3.1563	0.5257
0.0288	5.0	7815	3.4034	0.4951

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3