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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- amazon_reviews_multi |
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metrics: |
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- accuracy |
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- f1 |
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base_model: distilbert-base-multilingual-cased |
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model-index: |
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- name: distilbert-base-multilingual-cased-sentiment-2 |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: amazon_reviews_multi |
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type: amazon_reviews_multi |
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args: all_languages |
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metrics: |
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- type: accuracy |
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value: 0.7475666666666667 |
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name: Accuracy |
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- type: f1 |
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value: 0.7475666666666667 |
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name: F1 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilbert-base-multilingual-cased-sentiment-2 |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6067 |
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- Accuracy: 0.7476 |
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- F1: 0.7476 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00024 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 33 |
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- distributed_type: sagemaker_data_parallel |
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- num_devices: 8 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 0.6885 | 0.53 | 5000 | 0.6532 | 0.7217 | 0.7217 | |
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| 0.6411 | 1.07 | 10000 | 0.6348 | 0.7319 | 0.7319 | |
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| 0.6057 | 1.6 | 15000 | 0.6186 | 0.7387 | 0.7387 | |
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| 0.5844 | 2.13 | 20000 | 0.6236 | 0.7449 | 0.7449 | |
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| 0.549 | 2.67 | 25000 | 0.6067 | 0.7476 | 0.7476 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.1 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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