transformers pytorch distilbert fill-mask 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:
- accuracy
model-index:
- name: 20231008-3-distilbert-base-multilingual-cased-new
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 20231008-3-distilbert-base-multilingual-cased-new

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.5585
- Loss: 1.8969

## 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: 20

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 3.0355        | 1.82  | 200  | 0.3649   | 2.5361          |
| 2.5432        | 3.64  | 400  | 0.4264   | 2.4729          |
| 2.3986        | 5.45  | 600  | 0.4748   | 2.1543          |
| 2.2755        | 7.27  | 800  | 0.5533   | 1.9309          |
| 2.1743        | 9.09  | 1000 | 0.5165   | 2.1052          |
| 2.1152        | 10.91 | 1200 | 0.5307   | 2.0024          |
| 1.9368        | 12.73 | 1400 | 0.5820   | 1.7487          |
| 1.989         | 14.55 | 1600 | 0.5507   | 1.9093          |
| 1.8819        | 16.36 | 1800 | 0.5835   | 1.6382          |
| 1.8822        | 18.18 | 2000 | 0.5873   | 1.7373          |
| 1.8628        | 20.0  | 2200 | 0.5585   | 1.8969          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
