metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-sentiment-2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: amazon_reviews_multi
args: en
metrics:
- name: Accuracy
type: accuracy
value: 0.7614
- name: F1
type: f1
value: 0.7614
distilbert-base-multilingual-cased-sentiment-2
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: 0.5882
- Accuracy: 0.7614
- F1: 0.7614
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: 0.00024
- 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: 3
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.15.1
- Tokenizers 0.10.3