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bert-base-cased-qnli

WillHeld / bert-base-cased-qnli

Run on huggingface.co
huggingface.co
Total runs: 16
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: September 16 2022
text-classification

Introduction of bert-base-cased-qnli

Model Details of bert-base-cased-qnli

bert-base-cased-qnli

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

  • Loss: 0.2569
  • Accuracy: 0.9087
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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 10.0
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.6529 0.08 500 0.4945 0.7734
0.4731 0.15 1000 0.3888 0.8406
0.4113 0.23 1500 0.3605 0.8523
0.4006 0.31 2000 0.3175 0.8649
0.3615 0.38 2500 0.3220 0.8678
0.3662 0.46 3000 0.3198 0.8667
0.3578 0.53 3500 0.2970 0.8779
0.3349 0.61 4000 0.2864 0.8834
0.3548 0.69 4500 0.2664 0.8946
0.3254 0.76 5000 0.2651 0.8929
0.3212 0.84 5500 0.2943 0.8817
0.3195 0.92 6000 0.2630 0.8960
0.3044 0.99 6500 0.2766 0.8882
0.245 1.07 7000 0.3268 0.9013
0.2415 1.15 7500 0.2987 0.8991
0.248 1.22 8000 0.3373 0.8812
0.2328 1.3 8500 0.3474 0.8808
0.2427 1.37 9000 0.2986 0.8913
0.243 1.45 9500 0.2835 0.8982
0.2375 1.53 10000 0.2893 0.8909
0.2253 1.6 10500 0.2942 0.8960
0.2429 1.68 11000 0.2852 0.9028
0.238 1.76 11500 0.2672 0.9037
0.2344 1.83 12000 0.2672 0.9021
0.2368 1.91 12500 0.2754 0.9019
0.2424 1.99 13000 0.2569 0.9087
0.1542 2.06 13500 0.3807 0.9026
0.1416 2.14 14000 0.3915 0.8980
0.1445 2.21 14500 0.4292 0.8984
0.1631 2.29 15000 0.4097 0.8971
0.1512 2.37 15500 0.3880 0.9012
0.1624 2.44 16000 0.4083 0.8955
0.1616 2.52 16500 0.3950 0.9039
0.1587 2.6 17000 0.3579 0.9103
0.1615 2.67 17500 0.3931 0.9012
0.1623 2.75 18000 0.3697 0.9059
0.1687 2.83 18500 0.3473 0.9037
0.1627 2.9 19000 0.3851 0.8982
0.1593 2.98 19500 0.4039 0.9019
0.1136 3.05 20000 0.4835 0.9024
0.0965 3.13 20500 0.5061 0.9012
0.0931 3.21 21000 0.5279 0.8991
0.0993 3.28 21500 0.4856 0.9019
0.1187 3.36 22000 0.4883 0.9032
0.1008 3.44 22500 0.5054 0.9015
0.1013 3.51 23000 0.5025 0.9023
0.1092 3.59 23500 0.4485 0.8986
0.1135 3.67 24000 0.5123 0.8977
0.1042 3.74 24500 0.4884 0.9010
0.1178 3.82 25000 0.4130 0.9006
0.1041 3.89 25500 0.4847 0.8951
0.1025 3.97 26000 0.4706 0.8986
0.0833 4.05 26500 0.5018 0.9054
0.0632 4.12 27000 0.5426 0.9055
0.0613 4.2 27500 0.5629 0.9021
0.0703 4.28 28000 0.5763 0.9033
0.0687 4.35 28500 0.5274 0.9039
0.0707 4.43 29000 0.5682 0.9019
0.0717 4.51 29500 0.5382 0.9004
0.0692 4.58 30000 0.5901 0.9010
0.0701 4.66 30500 0.5817 0.8990
0.0708 4.73 31000 0.5580 0.9019
0.07 4.81 31500 0.5640 0.8990
0.0725 4.89 32000 0.5768 0.8993
0.0701 4.96 32500 0.5289 0.9035
0.0441 5.04 33000 0.6401 0.9010
0.0388 5.12 33500 0.6446 0.8991
0.0417 5.19 34000 0.6327 0.9039
0.039 5.27 34500 0.6385 0.9048
0.0407 5.35 35000 0.6510 0.9030
0.0446 5.42 35500 0.5788 0.9030
0.0422 5.5 36000 0.6723 0.9024
0.04 5.58 36500 0.6602 0.9037
0.0514 5.65 37000 0.6407 0.9024
0.0462 5.73 37500 0.6145 0.9048
0.0479 5.8 38000 0.5881 0.9008
0.0503 5.88 38500 0.6001 0.9008
0.0385 5.96 39000 0.6464 0.9052
0.0436 6.03 39500 0.6683 0.9039
0.0296 6.11 40000 0.6965 0.9037
0.0275 6.19 40500 0.7193 0.9039
0.0258 6.26 41000 0.7229 0.9039
0.0223 6.34 41500 0.6974 0.9074
0.0268 6.42 42000 0.7045 0.9028
0.0297 6.49 42500 0.7289 0.9055
0.0295 6.57 43000 0.6810 0.9050
0.0265 6.64 43500 0.6833 0.9065
0.0268 6.72 44000 0.7155 0.9035
0.0293 6.8 44500 0.7632 0.9015
0.0289 6.87 45000 0.7229 0.9033
0.0286 6.95 45500 0.6671 0.9054
0.024 7.03 46000 0.7659 0.9033
0.0141 7.1 46500 0.7981 0.9023
0.0212 7.18 47000 0.7021 0.9088
0.0183 7.26 47500 0.7122 0.9096
0.0221 7.33 48000 0.7080 0.9065
0.0146 7.41 48500 0.7344 0.9074
0.0181 7.48 49000 0.7273 0.9105
0.0161 7.56 49500 0.7332 0.9083
0.0193 7.64 50000 0.7117 0.9094
0.0165 7.71 50500 0.7797 0.9070
0.0173 7.79 51000 0.7128 0.9107
0.0158 7.87 51500 0.7420 0.9110
0.0157 7.94 52000 0.7198 0.9129
0.0142 8.02 52500 0.7033 0.9114
0.0107 8.1 53000 0.7761 0.9109
0.0122 8.17 53500 0.7777 0.9110
0.013 8.25 54000 0.7880 0.9076
0.0092 8.32 54500 0.8070 0.9074
0.0102 8.4 55000 0.8113 0.9055
0.0099 8.48 55500 0.8153 0.9079
0.0087 8.55 56000 0.8045 0.9112
0.0133 8.63 56500 0.8173 0.9081
0.017 8.71 57000 0.7646 0.9101
0.0093 8.78 57500 0.7681 0.9120
0.0085 8.86 58000 0.8067 0.9083
0.0137 8.94 58500 0.7645 0.9107
0.0099 9.01 59000 0.7742 0.9123
0.0074 9.09 59500 0.8052 0.9059
0.0057 9.16 60000 0.7906 0.9132
0.0046 9.24 60500 0.7915 0.9136
0.0036 9.32 61000 0.8114 0.9101
0.0036 9.39 61500 0.8382 0.9087
0.0079 9.47 62000 0.8013 0.9110
0.0079 9.55 62500 0.8116 0.9099
0.0054 9.62 63000 0.8143 0.9110
0.0036 9.7 63500 0.8138 0.9114
0.0053 9.78 64000 0.8158 0.9107
0.0035 9.85 64500 0.8146 0.9112
0.0051 9.93 65000 0.8168 0.9107
Framework versions
  • Transformers 4.21.3
  • Pytorch 1.7.1
  • Datasets 1.18.3
  • Tokenizers 0.11.6

Runs of WillHeld bert-base-cased-qnli on huggingface.co

16
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0
24-hour runs
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3-day runs
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7-day runs
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More Information About bert-base-cased-qnli huggingface.co Model

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https://choosealicense.com/licenses/apache-2.0

bert-base-cased-qnli huggingface.co

bert-base-cased-qnli huggingface.co is an AI model on huggingface.co that provides bert-base-cased-qnli's model effect (), which can be used instantly with this WillHeld bert-base-cased-qnli model. huggingface.co supports a free trial of the bert-base-cased-qnli model, and also provides paid use of the bert-base-cased-qnli. Support call bert-base-cased-qnli model through api, including Node.js, Python, http.

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WillHeld bert-base-cased-qnli online free

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https://huggingface.co/WillHeld/bert-base-cased-qnli

bert-base-cased-qnli install

bert-base-cased-qnli is an open source model from GitHub that offers a free installation service, and any user can find bert-base-cased-qnli on GitHub to install. At the same time, huggingface.co provides the effect of bert-base-cased-qnli install, users can directly use bert-base-cased-qnli installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

bert-base-cased-qnli install url in huggingface.co:

https://huggingface.co/WillHeld/bert-base-cased-qnli

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bert-base-cased-qnli huggingface.co Url

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WillHeld
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