Downloads · 30 days
0
Mistral-7B-Instruct-v0.3-lora-commonsense
yspkm/Mistral-7B-Instruct-v0.3-lora-commonsense
Mistral-7B-Instruct-v0.3-lora-commonsense is a machine learning model from yspkm. 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. --
Access
Public
Updated Jul 18, 2024
Parameters
83.9M
671 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin336 MB · 50%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024
- SHA
- 6b750f76
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-7B-Instruct-v0.3-lora-commonsense
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6863
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8738 | 0.1503 | 200 | 0.8158 |
| 0.8589 | 0.3006 | 400 | 0.7939 |
| 0.8589 | 0.4510 | 600 | 0.7800 |
| 0.8589 | 0.6013 | 800 | 0.7725 |
| 0.8305 | 0.7516 | 1000 | 0.7650 |
| 0.8331 | 0.9019 | 1200 | 0.7506 |
| 0.7808 | 1.0522 | 1400 | 0.7438 |
| 0.7781 | 1.2026 | 1600 | 0.7350 |
| 0.7647 | 1.3529 | 1800 | 0.7252 |
| 0.7651 | 1.5032 | 2000 | 0.7228 |
| 0.7522 | 1.6535 | 2200 | 0.7099 |
| 0.7587 | 1.8038 | 2400 | 0.6997 |
| 0.7383 | 1.9542 | 2600 | 0.6932 |
| 0.7071 | 2.1045 | 2800 | 0.6949 |
| 0.6919 | 2.2548 | 3000 | 0.6899 |
| 0.7136 | 2.4051 | 3200 | 0.6884 |
| 0.6912 | 2.5554 | 3400 | 0.6878 |
| 0.6889 | 2.7057 | 3600 | 0.6867 |
| 0.6862 | 2.8561 | 3800 | 0.6863 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- License
- apache-2.0
- Created
- Jul 18, 2024
- Updated
- Jul 18, 2024