|
--- |
|
base_model: meta-llama/Meta-Llama-3-8B |
|
library_name: peft |
|
license: llama3 |
|
metrics: |
|
- accuracy |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: Output_llama2_70-15-15 |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Output_llama2_70-15-15 |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6250 |
|
- Balanced Accuracy: 0.6326 |
|
- Accuracy: 0.6282 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:| |
|
| No log | 1.0 | 46 | 0.7111 | 0.5764 | 0.5641 | |
|
| No log | 2.0 | 92 | 0.7043 | 0.5656 | 0.5577 | |
|
| No log | 3.0 | 138 | 0.6619 | 0.5142 | 0.5192 | |
|
| No log | 4.0 | 184 | 0.7013 | 0.5595 | 0.5513 | |
|
| No log | 5.0 | 230 | 0.6493 | 0.5620 | 0.5577 | |
|
| No log | 6.0 | 276 | 0.6496 | 0.5671 | 0.5641 | |
|
| No log | 7.0 | 322 | 0.6466 | 0.5798 | 0.5769 | |
|
| No log | 8.0 | 368 | 0.6748 | 0.5527 | 0.5513 | |
|
| No log | 9.0 | 414 | 0.6551 | 0.5692 | 0.5705 | |
|
| No log | 10.0 | 460 | 0.6205 | 0.6063 | 0.5833 | |
|
| 0.6541 | 11.0 | 506 | 0.6537 | 0.6020 | 0.6026 | |
|
| 0.6541 | 12.0 | 552 | 0.6379 | 0.6167 | 0.6154 | |
|
| 0.6541 | 13.0 | 598 | 0.6243 | 0.6107 | 0.6026 | |
|
| 0.6541 | 14.0 | 644 | 0.6248 | 0.6074 | 0.6026 | |
|
| 0.6541 | 15.0 | 690 | 0.6172 | 0.6370 | 0.6218 | |
|
| 0.6541 | 16.0 | 736 | 0.6237 | 0.6202 | 0.6154 | |
|
| 0.6541 | 17.0 | 782 | 0.6308 | 0.6230 | 0.6218 | |
|
| 0.6541 | 18.0 | 828 | 0.6179 | 0.6319 | 0.6218 | |
|
| 0.6541 | 19.0 | 874 | 0.6252 | 0.6326 | 0.6282 | |
|
| 0.6541 | 20.0 | 920 | 0.6250 | 0.6326 | 0.6282 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.19.1 |
