pytorch bert token-classification dataset:cynthiachan/FeedRef_10pct transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cynthiachan/FeedRef_10pct
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: training_3
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: cynthiachan/FeedRef_10pct
      type: cynthiachan/FeedRef_10pct
      args: FeedRef_10pct
    metrics:
    - name: Precision
      type: precision
      value: 0.6786570743405276
    - name: Recall
      type: recall
      value: 0.8372781065088757
    - name: F1
      type: f1
      value: 0.7496688741721853
    - name: Accuracy
      type: accuracy
      value: 0.9678051829961355
---

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# training_3

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the cynthiachan/FeedRef_10pct dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1302
- Precision: 0.6787
- Recall: 0.8373
- F1: 0.7497
- Accuracy: 0.9678

## 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: 5e-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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3927        | 0.37  | 500  | 0.2362          | 0.2854    | 0.4112 | 0.3370 | 0.9431   |
| 0.1994        | 0.75  | 1000 | 0.1656          | 0.4762    | 0.6509 | 0.55   | 0.9550   |
| 0.1541        | 1.12  | 1500 | 0.1437          | 0.5608    | 0.7367 | 0.6368 | 0.9602   |
| 0.1275        | 1.5   | 2000 | 0.1497          | 0.6090    | 0.7604 | 0.6763 | 0.9638   |
| 0.1184        | 1.87  | 2500 | 0.1302          | 0.6787    | 0.8373 | 0.7497 | 0.9678   |
| 0.0753        | 2.25  | 3000 | 0.1375          | 0.7454    | 0.8314 | 0.7860 | 0.9698   |
| 0.0613        | 2.62  | 3500 | 0.1465          | 0.8254    | 0.8669 | 0.8456 | 0.9736   |
| 0.0577        | 3.0   | 4000 | 0.1334          | 0.8144    | 0.8698 | 0.8412 | 0.9746   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
