---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
model-index:
- name: mt5-small-gigatrue-layercut-D34567
  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-gigatrue-layercut-D34567

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1397

## 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: 0.0003
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 4.6975        | 0.1015 | 3000  | 3.3978          |
| 4.1322        | 0.2030 | 6000  | 3.2703          |
| 4.0527        | 0.3044 | 9000  | 3.2199          |
| 4.0192        | 0.4059 | 12000 | 3.1998          |
| 3.9961        | 0.5074 | 15000 | 3.1842          |
| 3.9855        | 0.6089 | 18000 | 3.1708          |
| 3.9778        | 0.7104 | 21000 | 3.1657          |
| 3.9738        | 0.8119 | 24000 | 3.1591          |
| 3.9667        | 0.9133 | 27000 | 3.1557          |
| 3.9645        | 1.0148 | 30000 | 3.1508          |
| 3.9621        | 1.1163 | 33000 | 3.1504          |
| 3.958         | 1.2178 | 36000 | 3.1464          |
| 3.9559        | 1.3193 | 39000 | 3.1444          |
| 3.9548        | 1.4207 | 42000 | 3.1443          |
| 3.955         | 1.5222 | 45000 | 3.1444          |
| 3.9507        | 1.6237 | 48000 | 3.1408          |
| 3.9532        | 1.7252 | 51000 | 3.1420          |
| 3.9477        | 1.8267 | 54000 | 3.1412          |
| 3.9508        | 1.9282 | 57000 | 3.1404          |
| 3.952         | 2.0296 | 60000 | 3.1410          |
| 3.952         | 2.1311 | 63000 | 3.1405          |
| 3.9482        | 2.2326 | 66000 | 3.1405          |
| 3.9507        | 2.3341 | 69000 | 3.1401          |
| 3.9472        | 2.4356 | 72000 | 3.1399          |
| 3.9516        | 2.5370 | 75000 | 3.1400          |
| 3.9522        | 2.6385 | 78000 | 3.1396          |
| 3.9481        | 2.7400 | 81000 | 3.1397          |
| 3.9483        | 2.8415 | 84000 | 3.1398          |
| 3.9487        | 2.9430 | 87000 | 3.1397          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.20.3