|
|
--- |
|
|
library_name: peft |
|
|
base_model: Anwaarma/edos_taskB_llama3b_merged2_FINAL |
|
|
tags: |
|
|
- base_model:adapter:Anwaarma/edos_taskB_llama3b_merged2_FINAL |
|
|
- lora |
|
|
- transformers |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: try1 |
|
|
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. --> |
|
|
|
|
|
# try1 |
|
|
|
|
|
This model is a fine-tuned version of [Anwaarma/edos_taskB_llama3b_merged2_FINAL](https://huggingface.co/Anwaarma/edos_taskB_llama3b_merged2_FINAL) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.0008 |
|
|
- Accuracy: 0.6330 |
|
|
- F1 Macro: 0.5964 |
|
|
- F1 Micro: 0.6330 |
|
|
|
|
|
## 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: 32 |
|
|
- eval_batch_size: 64 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 64 |
|
|
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.06 |
|
|
- num_epochs: 20 |
|
|
- label_smoothing_factor: 0.1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
|
|
|:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:--------:| |
|
|
| 1.1785 | 1.8598 | 100 | 1.3641 | 0.5597 | 0.5106 | 0.5597 | |
|
|
| 0.977 | 3.7103 | 200 | 1.2230 | 0.5905 | 0.5455 | 0.5905 | |
|
|
| 0.833 | 5.5607 | 300 | 1.0872 | 0.6193 | 0.5723 | 0.6193 | |
|
|
| 0.7542 | 7.4112 | 400 | 1.0395 | 0.6152 | 0.5523 | 0.6152 | |
|
|
| 0.727 | 9.2617 | 500 | 0.9886 | 0.6502 | 0.5612 | 0.6502 | |
|
|
| 0.7084 | 11.1121 | 600 | 0.9770 | 0.6523 | 0.5784 | 0.6523 | |
|
|
| 0.7088 | 12.9720 | 700 | 0.9677 | 0.6502 | 0.5786 | 0.6502 | |
|
|
| 0.7005 | 14.8224 | 800 | 0.9622 | 0.6523 | 0.5831 | 0.6523 | |
|
|
| 0.6984 | 16.6729 | 900 | 0.9635 | 0.6543 | 0.5847 | 0.6543 | |
|
|
| 0.6982 | 18.5234 | 1000 | 0.9632 | 0.6481 | 0.5721 | 0.6481 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.17.1 |
|
|
- Transformers 4.56.2 |
|
|
- Pytorch 2.8.0+cu126 |
|
|
- Datasets 4.1.1 |
|
|
- Tokenizers 0.22.0 |
