---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- pytorch
- amazon-rating
- DistilBERTForSequenceClassification
- generated_from_trainer
metrics:
- accuracy
- matthews_correlation
model-index:
- name: distilbert-base-amazon-multi
  results: []
datasets:
- mteb/amazon_reviews_multi
language:
- en
- de
- es
- fr
- ja
- zh
library_name: transformers
pipeline_tag: text-classification
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-amazon-multi

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the mteb/amazon_reviews_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9292
- Accuracy: 0.6055
- Matthews Correlation: 0.5072

## Training procedure

This model was fine tuned on Google Colab using a single **NVIDIA V100** GPU with 16GB of VRAM. It took around 13 hours to finish the finetuning of 10_000 steps.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 320
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100000

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Matthews Correlation |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:--------------------:|
| 1.0008        | 0.26  | 10000  | 1.0027          | 0.5616   | 0.4520               |
| 0.9545        | 0.51  | 20000  | 0.9705          | 0.5810   | 0.4788               |
| 0.9216        | 0.77  | 30000  | 0.9415          | 0.5883   | 0.4868               |
| 0.8765        | 1.03  | 40000  | 0.9495          | 0.5891   | 0.4871               |
| 0.8837        | 1.28  | 50000  | 0.9254          | 0.5992   | 0.4997               |
| 0.8753        | 1.54  | 60000  | 0.9199          | 0.6014   | 0.5029               |
| 0.8572        | 1.8   | 70000  | 0.9108          | 0.6090   | 0.5117               |
| 0.7851        | 2.05  | 80000  | 0.9276          | 0.6052   | 0.5066               |
| 0.7918        | 2.31  | 90000  | 0.9292          | 0.6055   | 0.5072               |
| 0.793         | 2.57  | 100000 | 0.9288          | 0.6064   | 0.5084               |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0