gokuls / hbertv2-Massive-intent_48_emb_compress

huggingface.co
Total runs: 21
24-hour runs: 0
7-day runs: 9
30-day runs: 15
Model's Last Updated: June 20 2023
text-classification

Introduction of hbertv2-Massive-intent_48_emb_compress

Model Details of hbertv2-Massive-intent_48_emb_compress

hbertv2-Massive-intent_48_emb_compress

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48 on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9335
  • Accuracy: 0.8490
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
2.2651 1.0 180 1.2606 0.6606
1.0649 2.0 360 1.0114 0.7383
0.7609 3.0 540 0.8142 0.7959
0.5705 4.0 720 0.8234 0.7919
0.4182 5.0 900 0.7970 0.8013
0.3164 6.0 1080 0.7823 0.8141
0.233 7.0 1260 0.8068 0.8151
0.1623 8.0 1440 0.8618 0.8234
0.1208 9.0 1620 0.8545 0.8239
0.0823 10.0 1800 0.9072 0.8288
0.0508 11.0 1980 0.8755 0.8431
0.0329 12.0 2160 0.9474 0.8318
0.0181 13.0 2340 0.9236 0.8436
0.0084 14.0 2520 0.9424 0.8470
0.0045 15.0 2700 0.9335 0.8490
Framework versions
  • Transformers 4.30.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.13.0
  • Tokenizers 0.13.3

Runs of gokuls hbertv2-Massive-intent_48_emb_compress on huggingface.co

21
Total runs
0
24-hour runs
1
3-day runs
9
7-day runs
15
30-day runs

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