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mistral_fine_tuned
Aishwarya-r/mistral_fine_tuned
mistral_fine_tuned is a machine learning model from Aishwarya-r. 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 6, 2024
- Updated
- Dec 7, 2024
- SHA
- c116f33d
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. -->
Trial_mistral_peft
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.0726
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2773 | 0.9730 | 27 | 1.3014 |
| 1.182 | 1.9820 | 55 | 1.1646 |
| 1.0775 | 2.9910 | 83 | 1.1148 |
| 0.9209 | 4.0 | 111 | 1.0893 |
| 1.0438 | 4.9730 | 138 | 1.0781 |
| 1.0562 | 5.9820 | 166 | 1.0740 |
| 0.961 | 6.9910 | 194 | 1.0722 |
| 1.0702 | 8.0 | 222 | 1.0722 |
| 0.951 | 8.9730 | 249 | 1.0726 |
| 1.0278 | 9.7297 | 270 | 1.0726 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Dec 6, 2024
- Updated
- Dec 7, 2024