---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-multilingual-cased
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: multilabel_lora_distilbert_runews_classifier_tuned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# multilabel_lora_distilbert_runews_classifier_tuned

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0019
- Accuracy: 0.8276
- F1: 0.8284
- Precision: 0.8317
- Recall: 0.8276

## 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: 0.0009143508688456378
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 91   | 0.5987          | 0.7634   | 0.7621 | 0.7648    | 0.7634 |
| No log        | 2.0   | 182  | 0.3768          | 0.8693   | 0.8698 | 0.8767    | 0.8693 |
| No log        | 3.0   | 273  | 0.2620          | 0.9065   | 0.9063 | 0.9093    | 0.9065 |
| No log        | 4.0   | 364  | 0.2427          | 0.9202   | 0.9203 | 0.9220    | 0.9202 |
| No log        | 5.0   | 455  | 0.2244          | 0.9367   | 0.9369 | 0.9387    | 0.9367 |
| 0.3641        | 6.0   | 546  | 0.2385          | 0.9491   | 0.9491 | 0.9495    | 0.9491 |
| 0.3641        | 7.0   | 637  | 0.2560          | 0.9464   | 0.9464 | 0.9465    | 0.9464 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1