---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-finetuned-psi-classification-oversampled-gpu
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-multilingual-cased-finetuned-psi-classification-oversampled-gpu

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: 0.0568
- Accuracy: 0.9872
- F1: 0.9872

## 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: 2e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2501        | 1.0   | 1076 | 0.0491          | 0.9864   | 0.9862 |
| 0.0672        | 2.0   | 2152 | 0.0581          | 0.9864   | 0.9863 |
| 0.0446        | 3.0   | 3228 | 0.0635          | 0.9779   | 0.9780 |
| 0.03          | 4.0   | 4304 | 0.0566          | 0.9881   | 0.9880 |
| 0.0273        | 5.0   | 5380 | 0.0568          | 0.9872   | 0.9872 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1