README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - sst2
metrics:
  - accuracy
model-index:
  - name: sentiment-model-saagie
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: sst2
          type: sst2
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7916666666666666

sentiment-model-saagie

This model is a fine-tuned version of prajjwal1/bert-tiny on the sst2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5457
• Accuracy: 0.7917

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5174	1.0	1500	0.4787	0.765
0.379	2.0	3000	0.5247	0.7867
0.3362	3.0	4500	0.5457	0.7917

Framework versions

• Transformers 4.18.0
• Pytorch 1.8.1
• Datasets 2.12.0
• Tokenizers 0.12.1