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---
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
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