gokuls / hbertv1-small-wt-48-Massive-intent-emb-comp

huggingface.co
Total runs: 14
24-hour runs: 0
7-day runs: -10
30-day runs: -4
Model's Last Updated: July 22 2023
text-classification

Introduction of hbertv1-small-wt-48-Massive-intent-emb-comp

Model Details of hbertv1-small-wt-48-Massive-intent-emb-comp

hbertv1-small-wt-48-Massive-intent-emb-comp

This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_small_emb_comp on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8462
  • Accuracy: 0.8505
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: 64
  • eval_batch_size: 64
  • seed: 33
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
Training results
Training Loss Epoch Step Validation Loss Accuracy
2.1467 1.0 180 1.0602 0.7393
0.8554 2.0 360 0.7646 0.7964
0.5593 3.0 540 0.6846 0.8239
0.3868 4.0 720 0.6673 0.8278
0.2613 5.0 900 0.6909 0.8259
0.1681 6.0 1080 0.7123 0.8278
0.1096 7.0 1260 0.7193 0.8318
0.0687 8.0 1440 0.7653 0.8337
0.0405 9.0 1620 0.7966 0.8308
0.0255 10.0 1800 0.8047 0.8441
0.0145 11.0 1980 0.8415 0.8426
0.0092 12.0 2160 0.8462 0.8505
0.0053 13.0 2340 0.8635 0.8465
0.0031 14.0 2520 0.8625 0.8475
0.0023 15.0 2700 0.8632 0.8480
Framework versions
  • Transformers 4.31.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of gokuls hbertv1-small-wt-48-Massive-intent-emb-comp on huggingface.co

14
Total runs
0
24-hour runs
-4
3-day runs
-10
7-day runs
-4
30-day runs

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