Edit model card

tamil-sentiment-distilbert

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

  • Loss: 1.0230
  • Accuracy: 0.665

Dataset Information

  • text: Tamil-English code-mixed comment.
  • label: list of the possible sentiments
    • LABEL_0: "Positive",
    • LABEL_1: "Negative",
    • LABEL_2: "Mixed_feelings",
    • LABEL_3: "unknown_state",
    • LABEL_4: "not-Tamil"

Intended uses & limitations

This model was just created for doing classification task on tamilmixsentiment dataset

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 0
  • 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
1.0442 1.0 250 0.9883 0.674
0.9227 2.0 500 0.9782 0.673
0.7591 3.0 750 1.0230 0.665

Framework versions

  • Transformers 4.9.2
  • Pytorch 1.9.0+cu102
  • Datasets 1.11.0
  • Tokenizers 0.10.3
Downloads last month
6
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.

Dataset used to train Vasanth/tamil-sentiment-distilbert