---
library_name: peft
license: apache-2.0
base_model: agemagician/mlong-t5-tglobal-base
tags:
- generated_from_trainer
model-index:
- name: amharic_summarization_lora_model_normalized
  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_summarization_lora_model_normalized

This model is a fine-tuned version of [agemagician/mlong-t5-tglobal-base](https://huggingface.co/agemagician/mlong-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9366

## 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.ADAFACTOR and the args are:
No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2261        | 0.4913 | 400  | 1.0317          |
| 1.1147        | 0.9826 | 800  | 0.9737          |
| 1.082         | 1.4729 | 1200 | 0.9517          |
| 1.0729        | 1.9642 | 1600 | 0.9467          |
| 1.062         | 2.4544 | 2000 | 0.9352          |
| 1.0552        | 2.9457 | 2400 | 0.9366          |


### Framework versions

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