---
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-small-finetuned-medium
  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-small-finetuned-medium

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: 3.9152

## 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 23.6513       | 0.4578 | 500  | 4.2624          |
| 22.3063       | 0.9155 | 1000 | 4.1012          |
| 21.6209       | 1.3726 | 1500 | 4.0121          |
| 21.1642       | 1.8304 | 2000 | 3.9515          |
| 21.0332       | 2.2875 | 2500 | 3.9277          |
| 20.8154       | 2.7453 | 3000 | 3.9152          |


### Framework versions

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