Downloads · 30 days
10
23% of all-time downloads
run-llama
Baidicoot/run-llama
run-llama is a machine learning model from Baidicoot. 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 llama3.1.
should probably proofread and complete it, then remove this comment. --
All-time downloads
44
Public
Repo size
84 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors84 MB · 90%
At a glance
- Library
- peft
- License
- llama3.1
- Access
- Public
- Created
- Aug 10, 2024
- Updated
- Aug 10, 2024
- SHA
- 9762256f
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. -->
run-llama
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4304
- Accuracy: 0.7917
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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.6426 | 0.1130 | 10 | 0.5625 | 0.6485 |
| 0.6074 | 0.2260 | 20 | 0.6319 | 0.5821 |
| 0.4355 | 0.3390 | 30 | 0.7153 | 0.4967 |
| 0.5957 | 0.4520 | 40 | 0.7569 | 0.4683 |
| 0.3984 | 0.5650 | 50 | 0.7431 | 0.4616 |
| 0.4795 | 0.9836 | 60 | 0.7361 | 0.4514 |
| 0.3154 | 1.1475 | 70 | 0.7292 | 0.4393 |
| 0.3086 | 1.3115 | 80 | 0.75 | 0.4339 |
| 0.499 | 1.4754 | 90 | 0.7569 | 0.4281 |
| 0.2642 | 1.6393 | 100 | 0.7847 | 0.4281 |
| 0.2173 | 1.8033 | 110 | 0.7708 | 0.4200 |
| 0.3281 | 1.9672 | 120 | 0.7847 | 0.4151 |
| 0.2329 | 3.4211 | 130 | 0.7847 | 0.4172 |
| 0.2891 | 3.6842 | 140 | 0.7847 | 0.4202 |
| 0.3906 | 3.9474 | 150 | 0.7708 | 0.4285 |
| 0.2373 | 4.1026 | 160 | 0.4338 | 0.7778 |
| 0.2144 | 4.3590 | 170 | 0.4312 | 0.7847 |
| 0.2715 | 4.6154 | 180 | 0.4300 | 0.7847 |
| 0.1855 | 4.8718 | 190 | 0.4327 | 0.7917 |
| 0.3506 | 5.1282 | 200 | 0.4304 | 0.7917 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- llama3.1
- Created
- Aug 10, 2024
- Updated
- Aug 10, 2024