---
license: cc-by-4.0
base_model: allegro/herbert-large-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: herbert-large-cased_ner
  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. -->

# herbert-large-cased_ner

This model is a fine-tuned version of [allegro/herbert-large-cased](https://huggingface.co/allegro/herbert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3281
- Precision: 0.9354
- Recall: 0.9326
- F1: 0.9337
- Accuracy: 0.9598

## 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: 16
- 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   | 438  | 0.2556          | 0.8915    | 0.8923 | 0.8918 | 0.9369   |
| 0.311         | 2.0   | 876  | 0.1920          | 0.9101    | 0.9107 | 0.9102 | 0.9473   |
| 0.1466        | 3.0   | 1314 | 0.2481          | 0.9050    | 0.9058 | 0.9048 | 0.9442   |
| 0.093         | 4.0   | 1752 | 0.2565          | 0.9187    | 0.9276 | 0.9229 | 0.9537   |
| 0.0584        | 5.0   | 2190 | 0.2620          | 0.9216    | 0.9306 | 0.9260 | 0.9543   |
| 0.037         | 6.0   | 2628 | 0.2891          | 0.9263    | 0.9310 | 0.9282 | 0.9533   |
| 0.0169        | 7.0   | 3066 | 0.3159          | 0.9288    | 0.9314 | 0.9300 | 0.9564   |
| 0.0123        | 8.0   | 3504 | 0.3317          | 0.9359    | 0.9348 | 0.9345 | 0.9606   |
| 0.0123        | 9.0   | 3942 | 0.3097          | 0.9357    | 0.9305 | 0.9327 | 0.9594   |
| 0.0048        | 10.0  | 4380 | 0.3281          | 0.9354    | 0.9326 | 0.9337 | 0.9598   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1