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Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests
mg11/Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests
Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests is a machine learning model from mg11. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Jul 12, 2024
- Updated
- Aug 19, 2024
- SHA
- 8098a6a8
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. -->
Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests
This model is a fine-tuned version of hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7458
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: 0.0003
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0583 | 0.0630 | 1 | 3.3171 |
| 3.2898 | 0.1260 | 2 | 1.8112 |
| 1.7495 | 0.1890 | 3 | 1.3350 |
| 1.3176 | 0.2520 | 4 | 5.6302 |
| 5.9627 | 0.3150 | 5 | 2.1688 |
| 2.1926 | 0.3780 | 6 | 1.4297 |
| 1.3724 | 0.4409 | 7 | 1.2279 |
| 1.2125 | 0.5039 | 8 | 0.9445 |
| 0.9749 | 0.5669 | 9 | 1.1901 |
| 1.2164 | 0.6299 | 10 | 0.9843 |
| 0.9808 | 0.6929 | 11 | 0.9213 |
| 0.8698 | 0.7559 | 12 | 0.8721 |
| 0.8668 | 0.8189 | 13 | 0.9308 |
| 0.8635 | 0.8819 | 14 | 0.8319 |
| 0.7789 | 0.9449 | 15 | 0.8164 |
| 0.7402 | 1.0079 | 16 | 0.8220 |
| 0.7312 | 1.0709 | 17 | 0.8305 |
| 0.7561 | 1.1339 | 18 | 0.9768 |
| 0.9879 | 1.1969 | 19 | 0.8437 |
| 0.7647 | 1.2598 | 20 | 0.8364 |
| 0.7093 | 1.3228 | 21 | 0.8028 |
| 0.7358 | 1.3858 | 22 | 0.8184 |
| 0.7301 | 1.4488 | 23 | 0.8050 |
| 0.7607 | 1.5118 | 24 | 0.7652 |
| 0.6892 | 1.5748 | 25 | 0.7317 |
| 0.7158 | 1.6378 | 26 | 0.7236 |
| 0.6701 | 1.7008 | 27 | 0.7130 |
| 0.6905 | 1.7638 | 28 | 0.7529 |
| 0.6791 | 1.8268 | 29 | 0.7813 |
| 0.7093 | 1.8898 | 30 | 0.7458 |
Framework versions
- PEFT 0.5.0
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.16.0
- Tokenizers 0.19.1
- Library
- peft
- Created
- Jul 12, 2024
- Updated
- Aug 19, 2024