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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fin
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fin6
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: fin
type: fin
config: default
split: train
args: default
metrics:
- name: Precision
type: precision
value: 0.8237410071942446
- name: Recall
type: recall
value: 0.9123505976095617
- name: F1
type: f1
value: 0.8657844990548205
- name: Accuracy
type: accuracy
value: 0.9836742353161944
---
<!-- 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. -->
# fin6
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the fin dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0732
- Precision: 0.8237
- Recall: 0.9124
- F1: 0.8658
- Accuracy: 0.9837
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 129 | 0.0922 | 0.6559 | 0.8127 | 0.7260 | 0.9739 |
| No log | 2.0 | 258 | 0.0471 | 0.8889 | 0.9243 | 0.9062 | 0.9910 |
| No log | 3.0 | 387 | 0.0620 | 0.8419 | 0.9124 | 0.8757 | 0.9825 |
| 0.0622 | 4.0 | 516 | 0.0651 | 0.8156 | 0.9163 | 0.8630 | 0.9805 |
| 0.0622 | 5.0 | 645 | 0.0508 | 0.8614 | 0.9163 | 0.8880 | 0.9872 |
| 0.0622 | 6.0 | 774 | 0.0467 | 0.8988 | 0.9203 | 0.9094 | 0.9916 |
| 0.0622 | 7.0 | 903 | 0.0713 | 0.8099 | 0.9163 | 0.8598 | 0.9822 |
| 0.0052 | 8.0 | 1032 | 0.0767 | 0.8214 | 0.9163 | 0.8663 | 0.9824 |
| 0.0052 | 9.0 | 1161 | 0.0739 | 0.8179 | 0.9124 | 0.8625 | 0.9831 |
| 0.0052 | 10.0 | 1290 | 0.0732 | 0.8237 | 0.9124 | 0.8658 | 0.9837 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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