NasimB / bert-concat

huggingface.co
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7-day runs: 0
30-day runs: 0
Model's Last Updated: June 19 2023
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Introduction of bert-concat

Model Details of bert-concat

bert-concat

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

  • Loss: 5.9507
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: 0.0005
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 14
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss
7.3397 0.25 500 6.6405
6.5835 0.51 1000 6.5183
6.4967 0.76 1500 6.4926
6.451 1.01 2000 6.4507
6.4104 1.26 2500 6.4097
6.3868 1.52 3000 6.4019
6.3717 1.77 3500 6.3789
6.3361 2.02 4000 6.3596
6.3099 2.28 4500 6.3345
6.2807 2.53 5000 6.3050
6.2578 2.78 5500 6.2843
6.2356 3.03 6000 6.2735
6.2017 3.29 6500 6.2527
6.1837 3.54 7000 6.2277
6.1682 3.79 7500 6.2102
6.1443 4.04 8000 6.1917
6.1128 4.3 8500 6.1767
6.1034 4.55 9000 6.1678
6.0838 4.8 9500 6.1552
6.0641 5.06 10000 6.1401
6.0417 5.31 10500 6.1350
6.0247 5.56 11000 6.1123
6.0125 5.81 11500 6.1082
6.0028 6.07 12000 6.1022
5.9788 6.32 12500 6.0895
5.9739 6.57 13000 6.0828
5.9545 6.83 13500 6.0687
5.9441 7.08 14000 6.0652
5.923 7.33 14500 6.0567
5.9115 7.58 15000 6.0492
5.9106 7.84 15500 6.0466
5.8943 8.09 16000 6.0315
5.8726 8.34 16500 6.0339
5.8665 8.59 17000 6.0243
5.8548 8.85 17500 6.0193
5.8431 9.1 18000 6.0111
5.8218 9.35 18500 6.0053
5.8193 9.61 19000 6.0026
5.8174 9.86 19500 5.9927
5.7954 10.11 20000 5.9873
5.7779 10.36 20500 5.9823
5.7749 10.62 21000 5.9799
5.7739 10.87 21500 5.9784
5.7582 11.12 22000 5.9757
5.7415 11.38 22500 5.9686
5.7467 11.63 23000 5.9650
5.7448 11.88 23500 5.9648
5.7372 12.13 24000 5.9585
5.7207 12.39 24500 5.9596
5.7264 12.64 25000 5.9546
5.7212 12.89 25500 5.9516
5.7142 13.14 26000 5.9553
5.7103 13.4 26500 5.9551
5.7093 13.65 27000 5.9527
5.7183 13.9 27500 5.9507
Framework versions
  • Transformers 4.26.1
  • Pytorch 1.11.0+cu113
  • Datasets 2.13.0
  • Tokenizers 0.13.3

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More Information About bert-concat huggingface.co Model

bert-concat huggingface.co

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

bert-concat huggingface.co Url

https://huggingface.co/NasimB/bert-concat

NasimB bert-concat online free

bert-concat huggingface.co is an online trial and call api platform, which integrates bert-concat's modeling effects, including api services, and provides a free online trial of bert-concat, you can try bert-concat online for free by clicking the link below.

NasimB bert-concat online free url in huggingface.co:

https://huggingface.co/NasimB/bert-concat

bert-concat install

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

bert-concat install url in huggingface.co:

https://huggingface.co/NasimB/bert-concat

Url of bert-concat

bert-concat huggingface.co Url

Provider of bert-concat huggingface.co

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