afaji / fresh-2-layer-swag

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: 0
30-day runs: -1
Model's Last Updated: March 12 2024
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Introduction of fresh-2-layer-swag

Model Details of fresh-2-layer-swag

fresh-2-layer-swag

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

  • Loss: 2.2180
  • Accuracy: 0.3081
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: 16
  • eval_batch_size: 16
  • seed: 321
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 63 1.3858 0.2172
No log 2.0 126 1.3860 0.2273
No log 3.0 189 1.4008 0.2424
No log 4.0 252 1.6880 0.2121
No log 5.0 315 1.7630 0.2222
No log 6.0 378 2.2180 0.3081
No log 7.0 441 2.7238 0.2727
0.7342 8.0 504 2.2261 0.2424
0.7342 9.0 567 3.3632 0.2475
0.7342 10.0 630 2.8625 0.2525
0.7342 11.0 693 2.8340 0.2677
0.7342 12.0 756 3.2504 0.2374
0.7342 13.0 819 3.2605 0.2727
0.7342 14.0 882 3.6696 0.2525
0.7342 15.0 945 3.5670 0.2374
0.0282 16.0 1008 3.8346 0.2677
0.0282 17.0 1071 3.7978 0.2727
0.0282 18.0 1134 3.7438 0.2677
0.0282 19.0 1197 3.7843 0.2727
0.0282 20.0 1260 3.8037 0.2626
Framework versions
  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.0

Runs of afaji fresh-2-layer-swag on huggingface.co

5
Total runs
0
24-hour runs
-1
3-day runs
0
7-day runs
-1
30-day runs

More Information About fresh-2-layer-swag huggingface.co Model

fresh-2-layer-swag huggingface.co

fresh-2-layer-swag huggingface.co is an AI model on huggingface.co that provides fresh-2-layer-swag's model effect (), which can be used instantly with this afaji fresh-2-layer-swag model. huggingface.co supports a free trial of the fresh-2-layer-swag model, and also provides paid use of the fresh-2-layer-swag. Support call fresh-2-layer-swag model through api, including Node.js, Python, http.

fresh-2-layer-swag huggingface.co Url

https://huggingface.co/afaji/fresh-2-layer-swag

afaji fresh-2-layer-swag online free

fresh-2-layer-swag huggingface.co is an online trial and call api platform, which integrates fresh-2-layer-swag's modeling effects, including api services, and provides a free online trial of fresh-2-layer-swag, you can try fresh-2-layer-swag online for free by clicking the link below.

afaji fresh-2-layer-swag online free url in huggingface.co:

https://huggingface.co/afaji/fresh-2-layer-swag

fresh-2-layer-swag install

fresh-2-layer-swag is an open source model from GitHub that offers a free installation service, and any user can find fresh-2-layer-swag on GitHub to install. At the same time, huggingface.co provides the effect of fresh-2-layer-swag install, users can directly use fresh-2-layer-swag installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

fresh-2-layer-swag install url in huggingface.co:

https://huggingface.co/afaji/fresh-2-layer-swag

Url of fresh-2-layer-swag

fresh-2-layer-swag huggingface.co Url

Provider of fresh-2-layer-swag huggingface.co

afaji
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