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mistral-journal-finetune
joy2000/mistral-journal-finetune
mistral-journal-finetune is a machine learning model from joy2000. 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
- Dec 18, 2023
- Updated
- Dec 31, 2023
- SHA
- 341f0818
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-journal-finetune
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6324
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9438 | 0.03 | 25 | 1.2268 |
| 1.1449 | 0.06 | 50 | 1.1088 |
| 1.1742 | 0.09 | 75 | 1.0455 |
| 1.0987 | 0.12 | 100 | 0.9922 |
| 1.0298 | 0.15 | 125 | 0.9476 |
| 0.9422 | 0.18 | 150 | 0.9082 |
| 0.934 | 0.21 | 175 | 0.8789 |
| 0.8254 | 0.24 | 200 | 0.8560 |
| 1.045 | 0.27 | 225 | 0.8217 |
| 0.9614 | 0.3 | 250 | 0.7783 |
| 0.8001 | 0.33 | 275 | 0.7525 |
| 0.8299 | 0.36 | 300 | 0.7238 |
| 0.7427 | 0.39 | 325 | 0.7087 |
| 0.7323 | 0.42 | 350 | 0.6973 |
| 0.7501 | 0.45 | 375 | 0.6794 |
| 0.819 | 0.48 | 400 | 0.6692 |
| 0.7871 | 0.51 | 425 | 0.6544 |
| 0.7604 | 0.54 | 450 | 0.6431 |
| 0.6955 | 0.57 | 475 | 0.6356 |
| 0.6919 | 0.6 | 500 | 0.6324 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- peft
- License
- apache-2.0
- Created
- Dec 18, 2023
- Updated
- Dec 31, 2023