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---
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
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