---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wnut_17
model-index:
- name: fine_tune_bert_output
  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. -->

# fine_tune_bert_output

This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3504
- Overall Precision: 0.6850
- Overall Recall: 0.6196
- Overall F1: 0.6507
- Overall Accuracy: 0.9502
- Corporation F1: 0.2626
- Creative-work F1: 0.4460
- Group F1: 0.3692
- Location F1: 0.7283
- Person F1: 0.7928
- Product F1: 0.3852

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Corporation F1 | Creative-work F1 | Group F1 | Location F1 | Person F1 | Product F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:--------:|:-----------:|:---------:|:----------:|
| 0.2954        | 1.0   | 213  | 0.4357          | 0.0               | 0.0            | 0.0        | 0.8979           | 0.0            | 0.0              | 0.0      | 0.0         | 0.0       | 0.0        |
| 0.1654        | 2.0   | 426  | 0.3435          | 0.5890            | 0.3929         | 0.4714     | 0.9307           | 0.0            | 0.0              | 0.0      | 0.4444      | 0.6181    | 0.0        |
| 0.1213        | 3.0   | 639  | 0.2981          | 0.6425            | 0.4776         | 0.5479     | 0.9380           | 0.1961         | 0.0565           | 0.1720   | 0.5507      | 0.7285    | 0.0        |
| 0.051         | 4.0   | 852  | 0.2958          | 0.7020            | 0.4892         | 0.5766     | 0.9430           | 0.2540         | 0.3458           | 0.2157   | 0.63        | 0.73      | 0.2388     |
| 0.0503        | 5.0   | 1065 | 0.3154          | 0.6659            | 0.5033         | 0.5733     | 0.9429           | 0.2373         | 0.3365           | 0.3212   | 0.6         | 0.7223    | 0.2896     |
| 0.026         | 6.0   | 1278 | 0.2787          | 0.6768            | 0.5706         | 0.6192     | 0.9479           | 0.256          | 0.4163           | 0.3699   | 0.7107      | 0.7717    | 0.3052     |
| 0.0271        | 7.0   | 1491 | 0.2940          | 0.7122            | 0.5714         | 0.6341     | 0.9486           | 0.25           | 0.3982           | 0.3676   | 0.7033      | 0.7717    | 0.3460     |
| 0.0239        | 8.0   | 1704 | 0.2872          | 0.6210            | 0.5839         | 0.6019     | 0.9461           | 0.2722         | 0.4188           | 0.2902   | 0.7389      | 0.7593    | 0.3597     |
| 0.0155        | 9.0   | 1917 | 0.2910          | 0.6863            | 0.5905         | 0.6348     | 0.9494           | 0.2623         | 0.4959           | 0.3433   | 0.6878      | 0.7708    | 0.3614     |
| 0.0122        | 10.0  | 2130 | 0.3067          | 0.6966            | 0.5797         | 0.6328     | 0.9490           | 0.2558         | 0.4609           | 0.3309   | 0.6842      | 0.7645    | 0.3835     |
| 0.0161        | 11.0  | 2343 | 0.2782          | 0.6637            | 0.6096         | 0.6355     | 0.9502           | 0.3103         | 0.4710           | 0.4275   | 0.6811      | 0.7688    | 0.4110     |
| 0.0232        | 12.0  | 2556 | 0.3123          | 0.6832            | 0.5822         | 0.6287     | 0.9495           | 0.3235         | 0.4722           | 0.4      | 0.7374      | 0.7568    | 0.4321     |
| 0.012         | 13.0  | 2769 | 0.3161          | 0.6663            | 0.5573         | 0.6070     | 0.9475           | 0.2128         | 0.4474           | 0.3289   | 0.7243      | 0.7400    | 0.4130     |
| 0.0051        | 14.0  | 2982 | 0.3241          | 0.7131            | 0.5864         | 0.6436     | 0.9498           | 0.3125         | 0.4839           | 0.3934   | 0.6952      | 0.7700    | 0.3802     |
| 0.0096        | 15.0  | 3195 | 0.3140          | 0.6924            | 0.6321         | 0.6609     | 0.9520           | 0.3036         | 0.4542           | 0.3576   | 0.7312      | 0.7953    | 0.432      |
| 0.0045        | 16.0  | 3408 | 0.3356          | 0.6917            | 0.6038         | 0.6448     | 0.9498           | 0.2899         | 0.4858           | 0.3582   | 0.6952      | 0.7840    | 0.4275     |
| 0.0066        | 17.0  | 3621 | 0.3308          | 0.6738            | 0.6262         | 0.6492     | 0.9510           | 0.2957         | 0.4333           | 0.3673   | 0.6989      | 0.7954    | 0.3320     |
| 0.0068        | 18.0  | 3834 | 0.3527          | 0.7157            | 0.6063         | 0.6565     | 0.9505           | 0.2353         | 0.4211           | 0.4058   | 0.7182      | 0.7991    | 0.3825     |
| 0.0033        | 19.0  | 4047 | 0.3522          | 0.7298            | 0.6013         | 0.6594     | 0.9514           | 0.2093         | 0.4454           | 0.4390   | 0.7006      | 0.7912    | 0.4000     |
| 0.0067        | 20.0  | 4260 | 0.3721          | 0.6859            | 0.5839         | 0.6308     | 0.9476           | 0.2774         | 0.3442           | 0.3881   | 0.7254      | 0.7844    | 0.3140     |
| 0.0083        | 21.0  | 4473 | 0.3504          | 0.6850            | 0.6196         | 0.6507     | 0.9502           | 0.2626         | 0.4460           | 0.3692   | 0.7283      | 0.7928    | 0.3852     |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6