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HW_llama3
davidcheng220/HW_llama3
HW_llama3 is a machine learning model from davidcheng220. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 17, 2024
- Updated
- Aug 17, 2024
- SHA
- 702bcb21
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. -->
HW_llama3
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.5763
- eval_matthews_correlation: 0.4248
- eval_runtime: 0.743
- eval_samples_per_second: 1403.799
- eval_steps_per_second: 88.831
- epoch: 1.0
- step: 2138
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: 1.6949202690971937e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 17, 2024
- Updated
- Aug 17, 2024