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custom_mistral_7b_orcawise_sep_27
Orcawise/custom_mistral_7b_orcawise_sep_27
custom_mistral_7b_orcawise_sep_27 is a machine learning model from Orcawise. 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
- Sep 27, 2024
- Updated
- Sep 27, 2024
- SHA
- a5b46b21
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 mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4476
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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 17
- training_steps: 1792
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.8156 | 0.1115 | 50 | 1.7682 |
| 1.6754 | 0.2230 | 100 | 1.6347 |
| 1.5257 | 0.3344 | 150 | 1.5543 |
| 1.5435 | 0.4459 | 200 | 1.5301 |
| 1.613 | 0.5574 | 250 | 1.5579 |
| 1.6178 | 0.6689 | 300 | 1.6006 |
| 1.675 | 0.7804 | 350 | 1.5209 |
| 1.5046 | 0.8919 | 400 | 1.5203 |
| 1.5977 | 1.0033 | 450 | 1.5253 |
| 1.5303 | 1.1148 | 500 | 1.4984 |
| 1.4748 | 1.2263 | 550 | 1.5073 |
| 1.4955 | 1.3378 | 600 | 1.4998 |
| 1.5737 | 1.4493 | 650 | 1.5405 |
| 1.5662 | 1.5608 | 700 | 1.5147 |
| 1.417 | 1.6722 | 750 | 1.5047 |
| 1.5732 | 1.7837 | 800 | 1.4768 |
| 1.5077 | 1.8952 | 850 | 1.4948 |
| 1.5634 | 2.0067 | 900 | 1.4768 |
| 1.5219 | 2.1182 | 950 | 1.4752 |
| 1.4073 | 2.2297 | 1000 | 1.4776 |
| 1.4915 | 2.3411 | 1050 | 1.4799 |
| 1.4585 | 2.4526 | 1100 | 1.4868 |
| 1.4979 | 2.5641 | 1150 | 1.4703 |
| 1.4755 | 2.6756 | 1200 | 1.4617 |
| 1.4167 | 2.7871 | 1250 | 1.4576 |
| 1.5095 | 2.8986 | 1300 | 1.4651 |
| 1.477 | 3.0100 | 1350 | 1.4526 |
| 1.4495 | 3.1215 | 1400 | 1.4660 |
| 1.5609 | 3.2330 | 1450 | 1.4547 |
| 1.4319 | 3.3445 | 1500 | 1.4478 |
| 1.3469 | 3.4560 | 1550 | 1.4597 |
| 1.4454 | 3.5674 | 1600 | 1.4478 |
| 1.4071 | 3.6789 | 1650 | 1.4506 |
| 1.3686 | 3.7904 | 1700 | 1.4485 |
| 1.4958 | 3.9019 | 1750 | 1.4476 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Sep 27, 2024
- Updated
- Sep 27, 2024