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
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Dataset used to train philschmid/distilbert-base-multilingual-cased-sentiment
Evaluation results
- Accuracy on amazon_reviews_multiself-reported0.765
- F1 on amazon_reviews_multiself-reported0.765