---
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