---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_classification_test
  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. -->

# token_classification_test

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2859
- Precision: 0.9187
- Recall: 0.9095
- F1: 0.9140
- Accuracy: 0.9308

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 47   | 1.2700          | 0.6758    | 0.5896 | 0.6298 | 0.7121   |
| No log        | 2.0   | 94   | 0.6468          | 0.8315    | 0.7864 | 0.8083 | 0.8461   |
| No log        | 3.0   | 141  | 0.4607          | 0.8709    | 0.8422 | 0.8563 | 0.8845   |
| No log        | 4.0   | 188  | 0.3841          | 0.8924    | 0.8686 | 0.8804 | 0.9047   |
| No log        | 5.0   | 235  | 0.3380          | 0.9060    | 0.8905 | 0.8982 | 0.9180   |
| No log        | 6.0   | 282  | 0.3164          | 0.9096    | 0.8934 | 0.9014 | 0.9213   |
| No log        | 7.0   | 329  | 0.3072          | 0.9090    | 0.9001 | 0.9045 | 0.9227   |
| No log        | 8.0   | 376  | 0.2997          | 0.9156    | 0.9009 | 0.9082 | 0.9258   |
| No log        | 9.0   | 423  | 0.2940          | 0.9141    | 0.9058 | 0.9099 | 0.9269   |
| No log        | 10.0  | 470  | 0.2904          | 0.9199    | 0.9076 | 0.9137 | 0.9312   |
| 0.5334        | 11.0  | 517  | 0.2894          | 0.9210    | 0.9093 | 0.9151 | 0.9314   |
| 0.5334        | 12.0  | 564  | 0.2884          | 0.9173    | 0.9081 | 0.9127 | 0.9295   |
| 0.5334        | 13.0  | 611  | 0.2862          | 0.9184    | 0.9089 | 0.9136 | 0.9305   |
| 0.5334        | 14.0  | 658  | 0.2859          | 0.9196    | 0.9103 | 0.9149 | 0.9310   |
| 0.5334        | 15.0  | 705  | 0.2859          | 0.9187    | 0.9095 | 0.9140 | 0.9308   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3