---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: balanced-augmented-bert-large-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-bert-large-gest-pred-seqeval-partialmatch-2

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4012
- Precision: 0.9108
- Recall: 0.9274
- F1: 0.9130
- Accuracy: 0.9045

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.9285        | 1.0   | 52   | 2.4277          | 0.2289    | 0.1482 | 0.1320 | 0.3077   |
| 1.9821        | 2.0   | 104  | 1.6710          | 0.5805    | 0.4849 | 0.4419 | 0.5576   |
| 1.3372        | 3.0   | 156  | 1.1456          | 0.6591    | 0.6279 | 0.6073 | 0.6703   |
| 0.8553        | 4.0   | 208  | 0.7989          | 0.7950    | 0.7956 | 0.7738 | 0.7864   |
| 0.4964        | 5.0   | 260  | 0.6153          | 0.8422    | 0.8447 | 0.8281 | 0.8378   |
| 0.2985        | 6.0   | 312  | 0.4399          | 0.9124    | 0.8982 | 0.8966 | 0.8814   |
| 0.1825        | 7.0   | 364  | 0.4938          | 0.8936    | 0.9034 | 0.8883 | 0.8829   |
| 0.1178        | 8.0   | 416  | 0.4713          | 0.9087    | 0.9188 | 0.9069 | 0.8912   |
| 0.0812        | 9.0   | 468  | 0.4012          | 0.9108    | 0.9274 | 0.9130 | 0.9045   |
| 0.0579        | 10.0  | 520  | 0.4695          | 0.9120    | 0.9132 | 0.9050 | 0.8942   |
| 0.0345        | 11.0  | 572  | 0.5327          | 0.9196    | 0.9165 | 0.9083 | 0.8976   |
| 0.0309        | 12.0  | 624  | 0.5243          | 0.9273    | 0.9207 | 0.9146 | 0.9025   |
| 0.0234        | 13.0  | 676  | 0.5089          | 0.9271    | 0.9243 | 0.9165 | 0.8996   |
| 0.0175        | 14.0  | 728  | 0.4750          | 0.9284    | 0.9258 | 0.9190 | 0.9059   |
| 0.015         | 15.0  | 780  | 0.4891          | 0.9310    | 0.9277 | 0.9210 | 0.9079   |
| 0.0109        | 16.0  | 832  | 0.5126          | 0.9240    | 0.9222 | 0.9153 | 0.9045   |
| 0.0085        | 17.0  | 884  | 0.4512          | 0.9320    | 0.9315 | 0.9246 | 0.9123   |
| 0.0077        | 18.0  | 936  | 0.5363          | 0.9241    | 0.9226 | 0.9149 | 0.9035   |
| 0.0058        | 19.0  | 988  | 0.5033          | 0.9246    | 0.9232 | 0.9156 | 0.9045   |
| 0.0062        | 20.0  | 1040 | 0.5066          | 0.9246    | 0.9232 | 0.9156 | 0.9045   |


### Framework versions

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