transformers tensorboard safetensors mt5 text2text-generation generated_from_trainer base_model:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
- wer
base_model: google/mt5-small
model-index:
- name: mt5_epoch_1To6
  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_epoch_1To6

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: nan
- Accuracy: 0.0
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Wer: 1.0
- Cer: 1.0
- Chrf: 0.0
- Exact Match: 0.0
- Bertscore:precision: 0.0
- Bertscore:recall: 0.0
- Bertscore:f1: 0.0
- Ter: 100.0
- Blerurt: -1.3889

## 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: 4
- eval_batch_size: 4
- 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: 5
- mixed_precision_training: Native AMP

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|:---:|:---:|:----:|:-----------:|:-------------------:|:----------------:|:------------:|:-----:|:-------:|
| 0.0           | 1.57  | 1000 | nan             | 0.0      | 0.0       | 0.0    | 0.0 | 1.0 | 1.0 | 0.0  | 0.0         | 0.0                 | 0.0              | 0.0          | 100.0 | -1.3889 |
| 0.0           | 3.14  | 2000 | nan             | 0.0      | 0.0       | 0.0    | 0.0 | 1.0 | 1.0 | 0.0  | 0.0         | 0.0                 | 0.0              | 0.0          | 100.0 | -1.3889 |
| 0.0           | 4.72  | 3000 | nan             | 0.0      | 0.0       | 0.0    | 0.0 | 1.0 | 1.0 | 0.0  | 0.0         | 0.0                 | 0.0              | 0.0          | 100.0 | -1.3889 |


### Framework versions

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