---
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_classifier_tuned_ru
  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_classifier_tuned_ru

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: 1.3658
- Accuracy: 0.7845
- F1: 0.7857
- Precision: 0.7997
- Recall: 0.7845

## 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: 4.993596574084884e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0622        | 1.0   | 727   | 0.9090          | 0.6025   | 0.5923 | 0.6149    | 0.6025 |
| 0.9449        | 2.0   | 1454  | 0.7451          | 0.6891   | 0.6855 | 0.6950    | 0.6891 |
| 0.7018        | 3.0   | 2181  | 0.6176          | 0.7359   | 0.7354 | 0.7377    | 0.7359 |
| 0.6192        | 4.0   | 2908  | 0.5854          | 0.7758   | 0.7751 | 0.7805    | 0.7758 |
| 0.4921        | 5.0   | 3635  | 0.5727          | 0.8061   | 0.8050 | 0.8202    | 0.8061 |
| 0.4091        | 6.0   | 4362  | 0.5019          | 0.8294   | 0.8293 | 0.8301    | 0.8294 |
| 0.3273        | 7.0   | 5089  | 0.4864          | 0.8404   | 0.8403 | 0.8409    | 0.8404 |
| 0.3473        | 8.0   | 5816  | 0.4828          | 0.8514   | 0.8512 | 0.8557    | 0.8514 |
| 0.2821        | 9.0   | 6543  | 0.4679          | 0.8597   | 0.8597 | 0.8597    | 0.8597 |
| 0.2599        | 10.0  | 7270  | 0.4874          | 0.8803   | 0.8799 | 0.8823    | 0.8803 |
| 0.2717        | 11.0  | 7997  | 0.4551          | 0.8831   | 0.8829 | 0.8832    | 0.8831 |
| 0.2211        | 12.0  | 8724  | 0.4602          | 0.8858   | 0.8856 | 0.8859    | 0.8858 |
| 0.2207        | 13.0  | 9451  | 0.5086          | 0.8845   | 0.8837 | 0.8862    | 0.8845 |
| 0.2166        | 14.0  | 10178 | 0.4795          | 0.8941   | 0.8936 | 0.8952    | 0.8941 |
| 0.1782        | 15.0  | 10905 | 0.4650          | 0.8955   | 0.8951 | 0.8959    | 0.8955 |


### Framework versions

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