---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
model-index:
- name: mt5-small-gigatrue-layercut-D5
  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-D5

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: 2.4092

## 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 3.6665        | 0.1015 | 3000  | 2.5503          |
| 3.1237        | 0.2030 | 6000  | 2.4814          |
| 3.0657        | 0.3044 | 9000  | 2.4631          |
| 3.0389        | 0.4059 | 12000 | 2.4435          |
| 3.0188        | 0.5074 | 15000 | 2.4455          |
| 3.0112        | 0.6089 | 18000 | 2.4229          |
| 3.0059        | 0.7104 | 21000 | 2.4302          |
| 3.0001        | 0.8119 | 24000 | 2.4221          |
| 2.994         | 0.9133 | 27000 | 2.4214          |
| 2.9932        | 1.0148 | 30000 | 2.4205          |
| 2.991         | 1.1163 | 33000 | 2.4148          |
| 2.9857        | 1.2178 | 36000 | 2.4131          |
| 2.985         | 1.3193 | 39000 | 2.4148          |
| 2.9831        | 1.4207 | 42000 | 2.4104          |
| 2.9842        | 1.5222 | 45000 | 2.4128          |
| 2.9785        | 1.6237 | 48000 | 2.4131          |
| 2.9817        | 1.7252 | 51000 | 2.4099          |
| 2.9754        | 1.8267 | 54000 | 2.4114          |
| 2.977         | 1.9282 | 57000 | 2.4088          |
| 2.9784        | 2.0296 | 60000 | 2.4082          |
| 2.9792        | 2.1311 | 63000 | 2.4095          |
| 2.9768        | 2.2326 | 66000 | 2.4102          |
| 2.9773        | 2.3341 | 69000 | 2.4096          |
| 2.9764        | 2.4356 | 72000 | 2.4085          |
| 2.9771        | 2.5370 | 75000 | 2.4076          |
| 2.9795        | 2.6385 | 78000 | 2.4085          |
| 2.9768        | 2.7400 | 81000 | 2.4088          |
| 2.9762        | 2.8415 | 84000 | 2.4093          |
| 2.9776        | 2.9430 | 87000 | 2.4092          |


### Framework versions

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