---
license: cc-by-4.0
base_model: Goader/liberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: liberta-large-topic_classification
  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-topic_classification

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: 0.7957
- Precision: 0.9167
- Recall: 0.8749
- F1: 0.8889
- Accuracy: 0.8971

## 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: 8
- 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   | 88   | 0.7214          | 0.8294    | 0.7438 | 0.7532 | 0.7843   |
| No log        | 2.0   | 176  | 0.6388          | 0.8181    | 0.7797 | 0.7826 | 0.8088   |
| No log        | 3.0   | 264  | 0.8149          | 0.8625    | 0.8692 | 0.8617 | 0.8725   |
| No log        | 4.0   | 352  | 0.8210          | 0.9171    | 0.8603 | 0.8695 | 0.8824   |
| No log        | 5.0   | 440  | 0.7850          | 0.9173    | 0.8700 | 0.8841 | 0.8922   |
| 0.3285        | 6.0   | 528  | 0.7936          | 0.8987    | 0.8670 | 0.8770 | 0.8824   |
| 0.3285        | 7.0   | 616  | 0.7794          | 0.9217    | 0.8749 | 0.8913 | 0.8971   |
| 0.3285        | 8.0   | 704  | 0.7835          | 0.9217    | 0.8749 | 0.8913 | 0.8971   |
| 0.3285        | 9.0   | 792  | 0.7947          | 0.9167    | 0.8749 | 0.8889 | 0.8971   |
| 0.3285        | 10.0  | 880  | 0.7957          | 0.9167    | 0.8749 | 0.8889 | 0.8971   |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.11.0a0+17540c5
- Datasets 2.21.0
- Tokenizers 0.15.2