Downloads · 30 days
5
26% of all-time downloads
ft-poc
Farisya/ft-poc
ft-poc is a machine learning model from Farisya. 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. --
All-time downloads
19
Public
Repo size
8.4 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors8.4 MB · 100%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Apr 1, 2024
- Updated
- Apr 1, 2024
- SHA
- 9316b780
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. -->
ft-poc
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5077
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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.6207 | 0.91 | 5 | 2.8472 |
| 2.1794 | 2.0 | 11 | 1.9461 |
| 1.8396 | 2.91 | 16 | 1.4070 |
| 1.0288 | 4.0 | 22 | 0.8795 |
| 0.7943 | 4.91 | 27 | 0.6335 |
| 0.5105 | 6.0 | 33 | 0.5606 |
| 0.5624 | 6.91 | 38 | 0.5307 |
| 0.4441 | 8.0 | 44 | 0.5145 |
| 0.5156 | 8.91 | 49 | 0.5080 |
| 0.2438 | 9.09 | 50 | 0.5077 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- peft
- License
- apache-2.0
- Created
- Apr 1, 2024
- Updated
- Apr 1, 2024