afaji / fresh-2-layer-medmcqa

huggingface.co
Total runs: 7
24-hour runs: 0
7-day runs: 0
30-day runs: 4
Model's Last Updated: March 11 2024
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Introduction of fresh-2-layer-medmcqa

Model Details of fresh-2-layer-medmcqa

fresh-2-layer-medmcqa

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

  • Loss: 2.0870
  • Accuracy: 0.2677
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 1.3865 0.2273
No log 2.0 126 1.3873 0.2273
No log 3.0 189 1.4299 0.1667
No log 4.0 252 1.4500 0.2071
No log 5.0 315 1.9720 0.2172
No log 6.0 378 2.0870 0.2677
No log 7.0 441 3.0344 0.2374
0.7594 8.0 504 2.8203 0.2222
0.7594 9.0 567 3.0874 0.2121
0.7594 10.0 630 3.1733 0.2525
0.7594 11.0 693 4.0368 0.1970
0.7594 12.0 756 4.1563 0.2273
0.7594 13.0 819 3.8739 0.2424
0.7594 14.0 882 3.6493 0.2576
0.7594 15.0 945 4.2385 0.2273
0.0675 16.0 1008 4.4551 0.2121
0.0675 17.0 1071 4.8175 0.2172
0.0675 18.0 1134 5.1875 0.2121
0.0675 19.0 1197 4.5584 0.2071
0.0675 20.0 1260 4.5618 0.2020
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-medmcqa on huggingface.co

7
Total runs
0
24-hour runs
-1
3-day runs
0
7-day runs
4
30-day runs

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

fresh-2-layer-medmcqa huggingface.co

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

fresh-2-layer-medmcqa huggingface.co Url

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

afaji fresh-2-layer-medmcqa online free

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

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

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

fresh-2-layer-medmcqa install

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

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

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

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afaji
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