---
license: apache-2.0
widget:
- text: I'm fine. Who is this?
- text: You can't take anything seriously.
- text: In the end he's going to croak, isn't he?
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: balanced-augmented-bert-gest-pred-seqeval-partialmatch
  results: []
pipeline_tag: token-classification
datasets:
- Jsevisal/balanced_augmented_dataset
---

<!-- 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-gest-pred-seqeval-partialmatch

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8382
- Precision: 0.8478
- Recall: 0.8224
- F1: 0.8293
- Accuracy: 0.8118

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 3.3729        | 1.0   | 32   | 2.8438          | 0.0806    | 0.0549 | 0.0294 | 0.1986   |
| 2.7169        | 2.0   | 64   | 2.2356          | 0.4355    | 0.2940 | 0.2982 | 0.4307   |
| 2.0107        | 3.0   | 96   | 1.7202          | 0.6950    | 0.5187 | 0.5245 | 0.5698   |
| 1.4085        | 4.0   | 128  | 1.3703          | 0.7994    | 0.6487 | 0.6499 | 0.6582   |
| 0.9974        | 5.0   | 160  | 1.1172          | 0.8205    | 0.7349 | 0.7514 | 0.7156   |
| 0.6996        | 6.0   | 192  | 1.0020          | 0.8220    | 0.7550 | 0.7684 | 0.7451   |
| 0.492         | 7.0   | 224  | 0.9132          | 0.8203    | 0.7626 | 0.7722 | 0.7549   |
| 0.3593        | 8.0   | 256  | 0.8785          | 0.8475    | 0.8042 | 0.8135 | 0.7921   |
| 0.2618        | 9.0   | 288  | 0.8383          | 0.8395    | 0.8135 | 0.8199 | 0.7999   |
| 0.1928        | 10.0  | 320  | 0.8410          | 0.8433    | 0.8165 | 0.8240 | 0.8014   |
| 0.1541        | 11.0  | 352  | 0.8382          | 0.8478    | 0.8224 | 0.8293 | 0.8118   |
| 0.1216        | 12.0  | 384  | 0.8667          | 0.8259    | 0.8253 | 0.8210 | 0.8046   |
| 0.096         | 13.0  | 416  | 0.8726          | 0.8471    | 0.8253 | 0.8301 | 0.8133   |
| 0.0767        | 14.0  | 448  | 0.8826          | 0.8475    | 0.8307 | 0.8330 | 0.8102   |
| 0.0696        | 15.0  | 480  | 0.8964          | 0.8411    | 0.8285 | 0.8303 | 0.8149   |
| 0.057         | 16.0  | 512  | 0.9194          | 0.8365    | 0.8292 | 0.8289 | 0.8097   |
| 0.0514        | 17.0  | 544  | 0.9085          | 0.8502    | 0.8277 | 0.8326 | 0.8118   |
| 0.0468        | 18.0  | 576  | 0.9261          | 0.8345    | 0.8250 | 0.8243 | 0.8092   |
| 0.0437        | 19.0  | 608  | 0.9279          | 0.8394    | 0.8258 | 0.8270 | 0.8118   |
| 0.0414        | 20.0  | 640  | 0.9263          | 0.8443    | 0.8275 | 0.8298 | 0.8139   |


### Framework versions

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