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mistral_instruct_generation
kaviani/mistral_instruct_generation
mistral_instruct_generation is a machine learning model from kaviani. 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
- Jul 22, 2024
- Updated
- Jul 23, 2024
- SHA
- 1ed1d230
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. -->
mistral_instruct_generation
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.6654
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: 0.0002
- 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_steps: 2
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9883 | 0.5882 | 10 | 1.8932 |
| 1.8095 | 1.1765 | 20 | 1.7633 |
| 1.6942 | 1.7647 | 30 | 1.7123 |
| 1.6099 | 2.3529 | 40 | 1.6814 |
| 1.5807 | 2.9412 | 50 | 1.6573 |
| 1.5032 | 3.5294 | 60 | 1.6472 |
| 1.4055 | 4.1176 | 70 | 1.6427 |
| 1.4101 | 4.7059 | 80 | 1.6471 |
| 1.3395 | 5.2941 | 90 | 1.6440 |
| 1.2556 | 5.8824 | 100 | 1.6654 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Jul 22, 2024
- Updated
- Jul 23, 2024