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WeniGPT-2.1.1-zephyr-7b-beta-BitsandBytes-LLM-Base-1.0.1-6k_Random_selection
Weni/WeniGPT-2.1.1-zephyr-7b-beta-BitsandBytes-LLM-Base-1.0.1-6k_Random_selection
WeniGPT-2.1.1-zephyr-7b-beta-BitsandBytes-LLM-Base-1.0.1-6k_Random_selection is a machine learning model from Weni. 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
- Model type
- mistral
- Access
- Public
- Created
- Jan 18, 2024
- Updated
- Jan 18, 2024
- SHA
- eead7289
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. -->
WeniGPT-2.1.1-zephyr-7b-beta-BitsandBytes-LLM-Base-1.0.1-6k_Random_selection
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.4532
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: 16
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 42
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.99 | 34 | 0.4548 |
| No log | 1.22 | 42 | 0.4532 |
Framework versions
- PEFT 0.7.1
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
- Library
- peft
- Type
- mistral
- License
- mit
- Created
- Jan 18, 2024
- Updated
- Jan 18, 2024