pytorch tensorboard bert token-classification transformers generated_from_trainer model-index autotrain_compatible
---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: 4L_weight_decay
  results: []
---

<!-- 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. -->

# 4L_weight_decay

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1312
- Precision: 0.7006
- Recall: 0.6863
- F1: 0.6934
- Accuracy: 0.9524

## 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: 3e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.157         | 1.0   | 5561  | 0.1464          | 0.6943    | 0.6153 | 0.6524 | 0.9465   |
| 0.1454        | 2.0   | 11122 | 0.1396          | 0.6921    | 0.6491 | 0.6699 | 0.9486   |
| 0.1414        | 3.0   | 16683 | 0.1372          | 0.6841    | 0.6746 | 0.6793 | 0.9492   |
| 0.1335        | 4.0   | 22244 | 0.1339          | 0.6997    | 0.6617 | 0.6802 | 0.9505   |
| 0.1308        | 5.0   | 27805 | 0.1339          | 0.6963    | 0.6763 | 0.6862 | 0.9510   |
| 0.1285        | 6.0   | 33366 | 0.1320          | 0.7102    | 0.6639 | 0.6863 | 0.9519   |
| 0.1257        | 7.0   | 38927 | 0.1306          | 0.7031    | 0.6771 | 0.6898 | 0.9521   |
| 0.1222        | 8.0   | 44488 | 0.1324          | 0.7005    | 0.6836 | 0.6919 | 0.9522   |
| 0.1207        | 9.0   | 50049 | 0.1313          | 0.7017    | 0.6832 | 0.6923 | 0.9524   |
| 0.1195        | 10.0  | 55610 | 0.1312          | 0.7006    | 0.6863 | 0.6934 | 0.9524   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
