---
library_name: peft
license: apache-2.0
base_model: google/mt5-small
tags:
- base_model:adapter:google/mt5-small
- lora
- transformers
model-index:
- name: mt5-finetuned-easy-v2
  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. -->

# mt5-finetuned-easy-v2

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9513

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAFACTOR and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 65.0991       | 0.4080 | 500  | 10.7504         |
| 34.0303       | 0.8160 | 1000 | 6.1853          |
| 28.7775       | 1.2236 | 1500 | 5.1882          |
| 27.4133       | 1.6316 | 2000 | 4.9513          |


### Framework versions

- PEFT 0.18.1
- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2