---
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: new2
  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. -->

# new2

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: 1.5177
- Accuracy: 0.5546
- F1 Macro: 0.5101
- F1 Micro: 0.5546

## 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: 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: 40
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.3186        | 1.8598 | 100  | 1.4746          | 0.5802   | 0.5325   | 0.5802   |
| 1.1161        | 3.7103 | 200  | 1.4088          | 0.5947   | 0.5390   | 0.5947   |
| 0.9134        | 5.5607 | 300  | 1.4204          | 0.5638   | 0.4999   | 0.5638   |
| 0.7884        | 7.4112 | 400  | 1.3747          | 0.5638   | 0.5132   | 0.5638   |
| 0.7428        | 9.2617 | 500  | 1.3314          | 0.5638   | 0.5076   | 0.5638   |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.0