README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - new_dataset
metrics:
  - accuracy
model-index:
  - name: sentiment-analysis-twitter
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: new_dataset
          type: new_dataset
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7965

sentiment-analysis-twitter

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the new_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.4579
• Accuracy: 0.7965

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: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5315	1.0	157	0.4517	0.788
0.388	2.0	314	0.4416	0.8
0.3307	3.0	471	0.4579	0.7965

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0+cu102
• Datasets 2.1.0
• Tokenizers 0.12.1