---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
- wer
base_model: google/mt5-small
model-index:
- name: nep-spell-mt5-small-0
  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. -->

# nep-spell-mt5-small-0

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: 1.6065
- Accuracy: 0.0
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Wer: 7.0137
- Cer: 13.4164
- Chrf: 1.5380
- Exact Match: 0.0
- Bertscore:precision: 0.4936
- Bertscore:recall: 0.5422
- Bertscore:f1: 0.5139
- Ter: 701.3722
- Blerurt: -0.5287

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1  | Wer     | Cer     | Chrf   | Exact Match | Bertscore:precision | Bertscore:recall | Bertscore:f1 | Ter       | Blerurt |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|:-------:|:-------:|:------:|:-----------:|:-------------------:|:----------------:|:------------:|:---------:|:-------:|
| 39.0737       | 0.39  | 500  | 14.0796         | 0.0      | 0.0       | 0.0    | 0.0 | 28.9335 | 58.5317 | 0.3292 | 0.0         | 0.3772              | 0.5413           | 0.4436       | 2893.3486 | -0.9012 |
| 4.5775        | 0.79  | 1000 | 1.6065          | 0.0      | 0.0       | 0.0    | 0.0 | 7.0137  | 13.4164 | 1.5380 | 0.0         | 0.4936              | 0.5422           | 0.5139       | 701.3722  | -0.5287 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2