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realDataFineTune
MichaelBr/realDataFineTune
realDataFineTune is a machine learning model from MichaelBr. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Jul 2, 2024
- Updated
- Jul 3, 2024
- SHA
- cbcd49dd
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
realDataFineTune
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 12.1175
- eval_runtime: 379.7612
- eval_samples_per_second: 15.407
- eval_steps_per_second: 3.852
- step: 0
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 20
- training_steps: 1000
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cpu
- Datasets 2.19.0
- Tokenizers 0.19.1
Training procedure
Framework versions
- PEFT 0.6.2
- Library
- peft
- License
- mit
- Created
- Jul 2, 2024
- Updated
- Jul 3, 2024