transformers tensorboard safetensors mt5 text2text-generation generated_from_trainer base_model:duraad/nep-spell-hft autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: duraad/nep-spell-hft
model-index:
- name: nep-spell-hft-993-01-05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# nep-spell-hft-993-01-05

This model is a fine-tuned version of [duraad/nep-spell-hft](https://huggingface.co/duraad/nep-spell-hft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.2828
- Precision: 0.2828
- Recall: 0.2828
- F1: 0.2828

## 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: 1e-06
- train_batch_size: 6
- eval_batch_size: 6
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0           | 0.75  | 100  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |
| 0.0           | 1.5   | 200  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |
| 0.0           | 2.26  | 300  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |
| 0.0           | 3.01  | 400  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |
| 0.0           | 3.76  | 500  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |
| 0.0           | 4.51  | 600  | nan             | 0.2828   | 0.2828    | 0.2828 | 0.2828 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
