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NXAIR_M_mistral-7B
codewizardUV/NXAIR_M_mistral-7B
NXAIR_M_mistral-7B is a machine learning model from codewizardUV. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 13, 2024
- Updated
- May 13, 2024
- SHA
- b55593df
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. -->
NXAIR_M_mistral-7B
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6929
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: 0.00025
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1435 | 0.0702 | 100 | 1.1971 |
| 1.0993 | 0.1404 | 200 | 1.0390 |
| 1.0643 | 0.2107 | 300 | 0.9309 |
| 0.956 | 0.2809 | 400 | 0.9125 |
| 0.9906 | 0.3511 | 500 | 0.8591 |
| 0.9083 | 0.4213 | 600 | 0.8703 |
| 0.8951 | 0.4916 | 700 | 0.8179 |
| 0.8352 | 0.5618 | 800 | 0.7852 |
| 0.8472 | 0.6320 | 900 | 0.7772 |
| 0.8733 | 0.7022 | 1000 | 0.7447 |
| 0.7958 | 0.7725 | 1100 | 0.7082 |
| 0.8726 | 0.8427 | 1200 | 0.7125 |
| 0.804 | 0.9129 | 1300 | 0.6909 |
| 0.8467 | 0.9831 | 1400 | 0.7287 |
| 0.4705 | 1.0534 | 1500 | 0.6921 |
| 0.4864 | 1.1236 | 1600 | 0.6648 |
| 0.4535 | 1.1938 | 1700 | 0.6765 |
| 0.4542 | 1.2640 | 1800 | 0.6620 |
| 0.4789 | 1.3343 | 1900 | 0.6584 |
| 0.5154 | 1.4045 | 2000 | 0.6492 |
| 0.459 | 1.4747 | 2100 | 0.6647 |
| 0.5168 | 1.5449 | 2200 | 0.6484 |
| 0.483 | 1.6152 | 2300 | 0.6795 |
| 0.4768 | 1.6854 | 2400 | 0.6730 |
| 0.4821 | 1.7556 | 2500 | 0.6404 |
| 0.4929 | 1.8258 | 2600 | 0.6409 |
| 0.5438 | 1.8961 | 2700 | 0.6551 |
| 0.4598 | 1.9663 | 2800 | 0.6740 |
| 0.4902 | 2.0365 | 2900 | 0.7287 |
| 0.5058 | 2.1067 | 3000 | 0.7142 |
| 0.4615 | 2.1770 | 3100 | 0.6929 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- May 13, 2024
- Updated
- May 13, 2024