afaji / fresh-2-layer-mmlu

huggingface.co
Total runs: 8
24-hour runs: 0
7-day runs: 4
30-day runs: 5
Model's Last Updated: March 16 2024
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Introduction of fresh-2-layer-mmlu

Model Details of fresh-2-layer-mmlu

fresh-2-layer-mmlu_EVAL_mmlu

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

  • Loss: 0.0196
  • Accuracy: 0.9942
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: 32
  • eval_batch_size: 32
  • 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 1.0 439 1.1960 0.518
1.2946 2.0 878 0.9728 0.61
1.1382 3.0 1317 0.6014 0.796
0.8904 4.0 1756 0.3594 0.88
0.5997 5.0 2195 0.2266 0.932
0.413 6.0 2634 0.1883 0.936
0.2801 7.0 3073 0.1547 0.95
0.2194 8.0 3512 0.1150 0.952
0.2194 9.0 3951 0.0860 0.974
0.1697 10.0 4390 0.0870 0.974
0.134 11.0 4829 0.0561 0.98
0.1098 12.0 5268 0.0450 0.99
0.0908 13.0 5707 0.0301 0.988
0.0771 14.0 6146 0.0229 0.992
0.0618 15.0 6585 0.0174 0.996
0.0482 16.0 7024 0.0107 0.998
0.0482 17.0 7463 0.0060 0.996
0.0418 18.0 7902 0.0037 0.998
0.0289 19.0 8341 0.0031 0.998
0.0242 20.0 8780 0.0029 0.998
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-mmlu on huggingface.co

8
Total runs
0
24-hour runs
0
3-day runs
4
7-day runs
5
30-day runs

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

fresh-2-layer-mmlu huggingface.co

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

fresh-2-layer-mmlu huggingface.co Url

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

afaji fresh-2-layer-mmlu online free

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

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

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

fresh-2-layer-mmlu install

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

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

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

Url of fresh-2-layer-mmlu

fresh-2-layer-mmlu huggingface.co Url

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afaji
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