---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
model-index:
- name: mt5-small-gigatrue-layercut-D456
  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-D456

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: 2.6214

## 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 4.249         | 0.1015 | 3000  | 2.7814          |
| 3.4936        | 0.2030 | 6000  | 2.7083          |
| 3.4312        | 0.3044 | 9000  | 2.6841          |
| 3.4015        | 0.4059 | 12000 | 2.6656          |
| 3.3795        | 0.5074 | 15000 | 2.6510          |
| 3.3716        | 0.6089 | 18000 | 2.6407          |
| 3.3644        | 0.7104 | 21000 | 2.6435          |
| 3.3595        | 0.8119 | 24000 | 2.6354          |
| 3.3534        | 0.9133 | 27000 | 2.6312          |
| 3.3522        | 1.0148 | 30000 | 2.6333          |
| 3.3501        | 1.1163 | 33000 | 2.6283          |
| 3.3451        | 1.2178 | 36000 | 2.6231          |
| 3.344         | 1.3193 | 39000 | 2.6240          |
| 3.3423        | 1.4207 | 42000 | 2.6217          |
| 3.3419        | 1.5222 | 45000 | 2.6252          |
| 3.3366        | 1.6237 | 48000 | 2.6247          |
| 3.3399        | 1.7252 | 51000 | 2.6215          |
| 3.3344        | 1.8267 | 54000 | 2.6219          |
| 3.337         | 1.9282 | 57000 | 2.6212          |
| 3.3394        | 2.0296 | 60000 | 2.6211          |
| 3.3393        | 2.1311 | 63000 | 2.6212          |
| 3.3353        | 2.2326 | 66000 | 2.6227          |
| 3.3369        | 2.3341 | 69000 | 2.6227          |
| 3.3348        | 2.4356 | 72000 | 2.6220          |
| 3.3358        | 2.5370 | 75000 | 2.6211          |
| 3.3377        | 2.6385 | 78000 | 2.6211          |
| 3.3336        | 2.7400 | 81000 | 2.6218          |
| 3.3359        | 2.8415 | 84000 | 2.6216          |
| 3.3368        | 2.9430 | 87000 | 2.6214          |


### Framework versions

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