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

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# distilbert-base-multilingual-cased-finetuned-geordie

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0262
- Precision: 0.9029
- Recall: 0.9162
- F1: 0.9095
- Accuracy: 0.9933

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.022         | 1.0   | 10080 | 0.0205          | 0.8689    | 0.9270 | 0.8970 | 0.9927   |
| 0.0156        | 2.0   | 20160 | 0.0203          | 0.9034    | 0.9072 | 0.9053 | 0.9930   |
| 0.0106        | 3.0   | 30240 | 0.0223          | 0.9010    | 0.9157 | 0.9083 | 0.9932   |
| 0.0082        | 4.0   | 40320 | 0.0262          | 0.9029    | 0.9162 | 0.9095 | 0.9933   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1