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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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