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

philschmid/distilbert-base-multilingual-cased-sentiment

distilbert-base-multilingual-cased-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

philschmid/
distilbert-base-multilingual-cased-sentiment