---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: balanced-augmented-distilbert-base-gest-pred-seqeval-partialmatch-2
  results: []
datasets:
- Jsevisal/balanced_augmented_dataset_2
pipeline_tag: token-classification
---

<!-- 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. -->

# balanced-augmented-distilbert-base-gest-pred-seqeval-partialmatch-2

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3958
- Precision: 0.9273
- Recall: 0.9067
- F1: 0.9116
- Accuracy: 0.9005

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 3.1391        | 1.0   | 52   | 2.5842          | 0.1830    | 0.1356 | 0.1249 | 0.3087   |
| 2.1708        | 2.0   | 104  | 1.7976          | 0.3943    | 0.3943 | 0.3622 | 0.5473   |
| 1.5993        | 3.0   | 156  | 1.3522          | 0.5329    | 0.4921 | 0.4697 | 0.6482   |
| 1.2237        | 4.0   | 208  | 1.1070          | 0.6701    | 0.5833 | 0.5820 | 0.6923   |
| 0.9516        | 5.0   | 260  | 0.9920          | 0.7506    | 0.6840 | 0.6820 | 0.7501   |
| 0.7364        | 6.0   | 312  | 0.7888          | 0.8171    | 0.7327 | 0.7350 | 0.7815   |
| 0.5816        | 7.0   | 364  | 0.6753          | 0.8510    | 0.7845 | 0.7961 | 0.8256   |
| 0.4507        | 8.0   | 416  | 0.5905          | 0.8807    | 0.8242 | 0.8400 | 0.8550   |
| 0.3589        | 9.0   | 468  | 0.5305          | 0.9021    | 0.8667 | 0.8746 | 0.8702   |
| 0.2875        | 10.0  | 520  | 0.5081          | 0.9176    | 0.8788 | 0.8911 | 0.8834   |
| 0.2268        | 11.0  | 572  | 0.4599          | 0.9133    | 0.8879 | 0.8939 | 0.8863   |
| 0.1875        | 12.0  | 624  | 0.4347          | 0.9224    | 0.8946 | 0.9025 | 0.8942   |
| 0.1608        | 13.0  | 676  | 0.4497          | 0.9186    | 0.8846 | 0.8956 | 0.8873   |
| 0.1356        | 14.0  | 728  | 0.4271          | 0.9242    | 0.8951 | 0.9038 | 0.8932   |
| 0.1197        | 15.0  | 780  | 0.3958          | 0.9273    | 0.9067 | 0.9116 | 0.9005   |
| 0.1015        | 16.0  | 832  | 0.4060          | 0.9285    | 0.9013 | 0.9095 | 0.8991   |
| 0.0896        | 17.0  | 884  | 0.4023          | 0.9300    | 0.9114 | 0.9157 | 0.9040   |
| 0.0847        | 18.0  | 936  | 0.4041          | 0.9296    | 0.9077 | 0.9133 | 0.9005   |
| 0.0811        | 19.0  | 988  | 0.4069          | 0.9291    | 0.9089 | 0.9133 | 0.9005   |
| 0.0752        | 20.0  | 1040 | 0.4086          | 0.9286    | 0.9075 | 0.9129 | 0.8996   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2