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_B05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT_B05

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: 0.3273
- Precision: 0.6078
- Recall: 0.6527
- F1: 0.6295
- Accuracy: 0.9042

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4541        | 1.0   | 92   | 0.3712          | 0.5576    | 0.5232 | 0.5399 | 0.8877   |
| 0.3098        | 2.0   | 184  | 0.3191          | 0.5546    | 0.6146 | 0.5831 | 0.8974   |
| 0.2016        | 3.0   | 276  | 0.3065          | 0.6049    | 0.6367 | 0.6204 | 0.9026   |
| 0.1919        | 4.0   | 368  | 0.3161          | 0.6148    | 0.6443 | 0.6292 | 0.9064   |
| 0.1387        | 5.0   | 460  | 0.3273          | 0.6078    | 0.6527 | 0.6295 | 0.9042   |


### Framework versions

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