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zephyr-finetuned-10epoch-NXAIR
Lalith16/zephyr-finetuned-10epoch-NXAIR
zephyr-finetuned-10epoch-NXAIR is a machine learning model from Lalith16. 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 mit.
should probably proofread and complete it, then remove this comment. --
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Updated Feb 5, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Feb 5, 2024
- Updated
- Feb 5, 2024
- SHA
- bdd2349b
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. -->
results
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0751
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: 2.5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2434 | 0.72 | 100 | 1.2548 |
| 0.772 | 1.45 | 200 | 0.8910 |
| 0.5866 | 2.17 | 300 | 0.8081 |
| 0.5755 | 2.9 | 400 | 0.7824 |
| 0.3935 | 3.62 | 500 | 0.8343 |
| 0.2616 | 4.35 | 600 | 0.8752 |
| 0.244 | 5.07 | 700 | 0.8777 |
| 0.2414 | 5.8 | 800 | 0.9291 |
| 0.19 | 6.52 | 900 | 1.0490 |
| 0.1828 | 7.25 | 1000 | 1.0226 |
| 0.1939 | 7.97 | 1100 | 1.0120 |
| 0.1647 | 8.7 | 1200 | 1.0177 |
| 0.1544 | 9.42 | 1300 | 1.0751 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- License
- mit
- Created
- Feb 5, 2024
- Updated
- Feb 5, 2024