---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_twitter_fine_tune
  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. -->

# ner_twitter_fine_tune

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4211
- Precision: 0.6078
- Recall: 0.5901
- F1: 0.5988
- Accuracy: 0.9308

## 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   | 56   | 0.3586          | 0.6358    | 0.5660 | 0.5989 | 0.9323   |
| No log        | 2.0   | 112  | 0.3618          | 0.6069    | 0.5746 | 0.5903 | 0.9297   |
| No log        | 3.0   | 168  | 0.3722          | 0.5956    | 0.6038 | 0.5997 | 0.9306   |
| No log        | 4.0   | 224  | 0.3993          | 0.6060    | 0.5883 | 0.5970 | 0.9301   |
| No log        | 5.0   | 280  | 0.4102          | 0.5411    | 0.6329 | 0.5834 | 0.9232   |
| No log        | 6.0   | 336  | 0.4077          | 0.6097    | 0.5815 | 0.5953 | 0.9319   |
| No log        | 7.0   | 392  | 0.4096          | 0.5858    | 0.6089 | 0.5971 | 0.9286   |
| No log        | 8.0   | 448  | 0.4169          | 0.5975    | 0.5832 | 0.5903 | 0.9297   |
| 0.0111        | 9.0   | 504  | 0.4208          | 0.6064    | 0.5866 | 0.5963 | 0.9309   |
| 0.0111        | 10.0  | 560  | 0.4211          | 0.6078    | 0.5901 | 0.5988 | 0.9308   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0
- Tokenizers 0.15.2