transformers safetensors distilbert token-classification generated_from_trainer base_model:mundo-go/my_ner_model license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: mundo-go/my_ner_model
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_ner_model
  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. -->

# my_ner_model

This model is a fine-tuned version of [mundo-go/my_ner_model](https://huggingface.co/mundo-go/my_ner_model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0000
- Recall: 1.0000
- F1: 1.0000
- Accuracy: 1.0000

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0015        | 1.0   | 1640 | 0.0001          | 0.9999    | 0.9999 | 0.9999 | 1.0000   |
| 0.0002        | 2.0   | 3280 | 0.0000          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
