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vicuna-qlora
chanchan7/vicuna-qlora
vicuna-qlora is a machine learning model from chanchan7. 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 llama2.
should probably proofread and complete it, then remove this comment. --
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Repo size
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At a glance
- Library
- peft
- License
- llama2
- Model type
- llama
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- Mar 4, 2024
- SHA
- 7f72ba2e
Base models
Datasets
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. -->
vicuna-qlora
This model is a fine-tuned version of lmsys/vicuna-7b-v1.5 on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 0.9819
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9771 | 1.0 | 570 | 0.9819 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
- Library
- peft
- Type
- llama
- License
- llama2
- Created
- Mar 3, 2024
- Updated
- Mar 4, 2024