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mistral-try-finetune
Sneka/mistral-try-finetune
mistral-try-finetune is a machine learning model from Sneka. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 24, 2023
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85.1 MB
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 24, 2023
- Updated
- Nov 24, 2023
- SHA
- 9bf072d3
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. -->
mistral-try-finetune
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3805
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: 2
- eval_batch_size: 8
- seed: 18
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 5
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5606 | 0.57 | 50 | 0.8581 |
| 0.5656 | 1.14 | 100 | 0.5153 |
| 0.3651 | 1.71 | 150 | 0.4257 |
| 0.2995 | 2.29 | 200 | 0.3750 |
| 0.2008 | 2.86 | 250 | 0.3405 |
| 0.1693 | 3.43 | 300 | 0.3282 |
| 0.144 | 4.0 | 350 | 0.3156 |
| 0.1112 | 4.57 | 400 | 0.3209 |
| 0.0949 | 5.14 | 450 | 0.3346 |
| 0.0801 | 5.71 | 500 | 0.3212 |
| 0.0717 | 6.29 | 550 | 0.3288 |
| 0.0579 | 6.86 | 600 | 0.3255 |
| 0.0486 | 7.43 | 650 | 0.3359 |
| 0.0495 | 8.0 | 700 | 0.3273 |
| 0.0374 | 8.57 | 750 | 0.3617 |
| 0.0377 | 9.14 | 800 | 0.3725 |
| 0.0324 | 9.71 | 850 | 0.3697 |
| 0.0338 | 10.29 | 900 | 0.3946 |
| 0.0305 | 10.86 | 950 | 0.3605 |
| 0.0289 | 11.43 | 1000 | 0.3805 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Nov 24, 2023
- Updated
- Nov 24, 2023