---
library_name: transformers
license: cc-by-4.0
base_model: Goader/liberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: liberta-large_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. -->

# liberta-large_ner

This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3665
- Precision: 0.9206
- Recall: 0.9363
- F1: 0.9275
- Accuracy: 0.9548

## 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  | 0.2759          | 0.8856    | 0.9109 | 0.8963 | 0.9300   |
| 0.3117        | 2.0   | 876  | 0.2289          | 0.9165    | 0.9251 | 0.9201 | 0.9493   |
| 0.1293        | 3.0   | 1314 | 0.3084          | 0.9111    | 0.9205 | 0.9147 | 0.9465   |
| 0.0687        | 4.0   | 1752 | 0.2430          | 0.9171    | 0.9343 | 0.9249 | 0.9534   |
| 0.0399        | 5.0   | 2190 | 0.2581          | 0.9284    | 0.9334 | 0.9292 | 0.9564   |
| 0.0223        | 6.0   | 2628 | 0.2819          | 0.9258    | 0.9368 | 0.9301 | 0.9563   |
| 0.0149        | 7.0   | 3066 | 0.3421          | 0.9158    | 0.9354 | 0.9252 | 0.9527   |
| 0.005         | 8.0   | 3504 | 0.3694          | 0.9162    | 0.9337 | 0.9238 | 0.9527   |
| 0.005         | 9.0   | 3942 | 0.3357          | 0.9241    | 0.9387 | 0.9308 | 0.9563   |
| 0.0029        | 10.0  | 4380 | 0.3665          | 0.9206    | 0.9363 | 0.9275 | 0.9548   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1