metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: amazon_reviews_multi
args: all_languages
metrics:
- name: Accuracy
type: accuracy
value: 0.7648
- name: F1
type: f1
value: 0.7648
distilbert-base-multilingual-cased-sentiment
This model is a fine-tuned version of distilbert-base-multilingual-cased on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:
- Loss: 0.5842
- Accuracy: 0.7648
- F1: 0.7648
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- distributed_type: sagemaker_data_parallel
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6405 | 0.53 | 5000 | 0.5826 | 0.7498 | 0.7498 |
| 0.5698 | 1.07 | 10000 | 0.5686 | 0.7612 | 0.7612 |
| 0.5286 | 1.6 | 15000 | 0.5593 | 0.7636 | 0.7636 |
| 0.5141 | 2.13 | 20000 | 0.5842 | 0.7648 | 0.7648 |
| 0.4763 | 2.67 | 25000 | 0.5736 | 0.7637 | 0.7637 |
| 0.4549 | 3.2 | 30000 | 0.6027 | 0.7593 | 0.7593 |
| 0.4231 | 3.73 | 35000 | 0.6017 | 0.7552 | 0.7552 |
| 0.3965 | 4.27 | 40000 | 0.6489 | 0.7551 | 0.7551 |
| 0.3744 | 4.8 | 45000 | 0.6426 | 0.7534 | 0.7534 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.15.1
- Tokenizers 0.10.3