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---
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 |