---
library_name: peft
license: gemma
base_model: google/gemma-3-4b-it
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: amharic_gemma_sum_lora_unnormalized
  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. -->

# amharic_gemma_sum_lora_unnormalized

This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2929

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4819        | 0.4913 | 400  | 1.4782          |
| 1.3682        | 0.9826 | 800  | 1.3819          |
| 1.3156        | 1.4729 | 1200 | 1.3339          |
| 1.2903        | 1.9642 | 1600 | 1.3070          |
| 1.2447        | 2.4544 | 2000 | 1.2958          |
| 1.2669        | 2.9457 | 2400 | 1.2929          |


### Framework versions

- PEFT 0.14.1.dev0
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.22.1