transformers pytorch distilbert token-classification generated_from_trainer base_model:distilbert-base-multilingual-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_B06
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT_B06

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: 0.2194
- Precision: 0.6602
- Recall: 0.7091
- F1: 0.6837
- Accuracy: 0.9351

## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4915        | 1.0   | 46   | 0.3346          | 0.5142    | 0.5049 | 0.5095 | 0.9013   |
| 0.2895        | 2.0   | 92   | 0.2445          | 0.6164    | 0.6517 | 0.6336 | 0.9235   |
| 0.1661        | 3.0   | 138  | 0.2254          | 0.6375    | 0.6937 | 0.6644 | 0.9321   |
| 0.1329        | 4.0   | 184  | 0.2213          | 0.6596    | 0.6993 | 0.6789 | 0.9331   |
| 0.1214        | 5.0   | 230  | 0.2194          | 0.6602    | 0.7091 | 0.6837 | 0.9351   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
