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---
library_name: transformers
license: cc-by-4.0
base_model: Goader/liberta-large
tags:
- generated_from_trainer
datasets:
- universal_dependencies
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: liberta-large-upos
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: universal_dependencies
type: universal_dependencies
config: uk_iu
split: validation
args: uk_iu
metrics:
- name: Precision
type: precision
value: 0.8100632457506624
- name: Recall
type: recall
value: 0.7466487546768732
- name: F1
type: f1
value: 0.7541998712736135
- name: Accuracy
type: accuracy
value: 0.8675486133248327
---
<!-- 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-upos
This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on the universal_dependencies dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3346
- Precision: 0.8101
- Recall: 0.7466
- F1: 0.7542
- Accuracy: 0.8675
## 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 | 338 | 1.0412 | 0.5939 | 0.4306 | 0.4617 | 0.5790 |
| No log | 2.0 | 676 | 0.6850 | 0.6114 | 0.5788 | 0.5745 | 0.7115 |
| No log | 3.0 | 1014 | 0.6075 | 0.6787 | 0.6205 | 0.6241 | 0.7389 |
| No log | 4.0 | 1352 | 0.5585 | 0.7178 | 0.6393 | 0.6425 | 0.7608 |
| No log | 5.0 | 1690 | 0.4762 | 0.7424 | 0.6737 | 0.6874 | 0.7984 |
| No log | 6.0 | 2028 | 0.4203 | 0.7159 | 0.6962 | 0.6946 | 0.8228 |
| No log | 7.0 | 2366 | 0.4275 | 0.7403 | 0.7081 | 0.7028 | 0.8205 |
| No log | 8.0 | 2704 | 0.3789 | 0.7909 | 0.7189 | 0.7282 | 0.8470 |
| No log | 9.0 | 3042 | 0.3431 | 0.8051 | 0.7415 | 0.7484 | 0.8626 |
| No log | 10.0 | 3380 | 0.3346 | 0.8101 | 0.7466 | 0.7542 | 0.8675 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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