README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
base_model: albert-base-v2
model-index:
  - name: albert-base-v2-imdb-calssification
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: imdb
          type: imdb
          args: plain_text
        metrics:
          - type: accuracy
            value: 0.93612
            name: Accuracy

albert-base-v2-imdb-calssification

label_0: negative label_1: positive

This model is a fine-tuned version of albert-base-v2 on the imdb dataset. It achieves the following results on the evaluation set:

• Loss: 0.1983
• Accuracy: 0.9361

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
• 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
• lr_scheduler_warmup_steps: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.26	1.0	1563	0.1983	0.9361

Framework versions

• Transformers 4.12.3
• Pytorch 1.10.0+cu111
• Datasets 1.15.1
• Tokenizers 0.10.3