Edit model card

tweet_sentiments_analysis_distilbert

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

  • Loss: 0.6626
  • F1-score: 0.7326

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: 5

Training results

Training Loss Epoch Step Validation Loss F1-score
0.7194 1.0 1000 0.6968 0.6919
0.5877 2.0 2000 0.6626 0.7326
0.4534 3.0 3000 0.8162 0.7333
0.2909 4.0 4000 1.0658 0.7436
0.2013 5.0 5000 1.3059 0.7409

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.0
  • Tokenizers 0.13.3
Downloads last month
20
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Jedida/tweet_sentiments_analysis_distilbert

Finetuned
(222)
this model