sentence-transformers-msmarco-distilbert-base-tas-b-twitter_sentiment

This model is a fine-tuned version of sentence-transformers/msmarco-distilbert-base-tas-b on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6954
  • Accuracy: 0.7146

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: 1e-06
  • 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8892 1.0 1387 0.8472 0.6180
0.7965 2.0 2774 0.7797 0.6609
0.7459 3.0 4161 0.7326 0.6872
0.7096 4.0 5548 0.7133 0.6995
0.6853 5.0 6935 0.6998 0.7002
0.6561 6.0 8322 0.6949 0.7059
0.663 7.0 9709 0.6956 0.7077
0.6352 8.0 11096 0.6890 0.7164
0.6205 9.0 12483 0.6888 0.7117
0.6203 10.0 13870 0.6871 0.7121
0.6005 11.0 15257 0.6879 0.7171
0.5985 12.0 16644 0.6870 0.7139
0.5839 13.0 18031 0.6882 0.7164
0.5861 14.0 19418 0.6910 0.7124
0.5732 15.0 20805 0.6916 0.7153
0.5797 16.0 22192 0.6947 0.7110
0.5565 17.0 23579 0.6930 0.7175
0.5636 18.0 24966 0.6959 0.7106
0.5642 19.0 26353 0.6952 0.7132
0.5717 20.0 27740 0.6954 0.7146

Framework versions

  • Transformers 4.13.0.dev0
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3
Downloads last month
259
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.