
<!-- 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. -->

# output_dir_nlpA

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0719
- Precision: 0.8688
- Recall: 0.8863
- F1: 0.8775
- Accuracy: 0.9747

## 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: 0.00023562901531222485
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.114         | 0.12  | 500  | 0.1153          | 0.8189    | 0.7594 | 0.7880 | 0.9607   |
| 0.0973        | 0.24  | 1000 | 0.1092          | 0.7920    | 0.8177 | 0.8047 | 0.9614   |
| 0.088         | 0.37  | 1500 | 0.0954          | 0.8387    | 0.8284 | 0.8335 | 0.9674   |
| 0.0744        | 0.49  | 2000 | 0.0883          | 0.8630    | 0.8248 | 0.8434 | 0.9694   |
| 0.06          | 0.61  | 2500 | 0.0853          | 0.8307    | 0.8833 | 0.8562 | 0.9703   |
| 0.0509        | 0.73  | 3000 | 0.0783          | 0.8657    | 0.8724 | 0.8690 | 0.9729   |
| 0.0422        | 0.85  | 3500 | 0.0753          | 0.8598    | 0.8875 | 0.8734 | 0.9738   |
| 0.0392        | 0.97  | 4000 | 0.0719          | 0.8688    | 0.8863 | 0.8775 | 0.9747   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "output_dir_nlpA", "results": []}]}
transformers safetensors bert token-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us