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zephyr-rag-agent
erbacher/zephyr-rag-agent
zephyr-rag-agent is a machine learning model from erbacher. 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
- May 13, 2024
- Updated
- May 14, 2024
- SHA
- a23b3238
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. -->
zephyr-rag-agent
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the erbacher/rag-and-roll dataset. It achieves the following results on the evaluation set:
- Loss: 1.1829
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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1559 | 0.99 | 27 | 1.1650 |
| 1.0887 | 1.98 | 54 | 1.1555 |
| 1.0566 | 2.97 | 81 | 1.1623 |
| 1.0264 | 6.95 | 91 | 1.1689 |
| 0.9977 | 7.97 | 105 | 1.1779 |
| 0.9808 | 9.0 | 119 | 1.1820 |
| 0.9791 | 9.8 | 130 | 1.1829 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.2.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
- Library
- peft
- Type
- mistral
- License
- mit
- Created
- May 13, 2024
- Updated
- May 14, 2024