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--- |
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license: mit |
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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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- precision |
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- recall |
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model-index: |
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- name: multi-minilm-finetuned-amazon-review |
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results: |
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- task: |
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name: Text Classification |
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type: 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: es |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5422 |
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- name: F1 |
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type: f1 |
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value: 0.543454465221178 |
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- name: Precision |
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type: precision |
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value: 0.5452336215624385 |
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- name: Recall |
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type: recall |
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value: 0.5422 |
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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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# multi-minilm-finetuned-amazon-review |
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This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2436 |
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- Accuracy: 0.5422 |
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- F1: 0.5435 |
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- Precision: 0.5452 |
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- Recall: 0.5422 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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- num_epochs: 5 |
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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 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.0049 | 1.0 | 2500 | 1.0616 | 0.5352 | 0.5268 | 0.5347 | 0.5352 | |
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| 0.9172 | 2.0 | 5000 | 1.0763 | 0.5432 | 0.5412 | 0.5444 | 0.5432 | |
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| 0.8285 | 3.0 | 7500 | 1.1077 | 0.5408 | 0.5428 | 0.5494 | 0.5408 | |
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| 0.7361 | 4.0 | 10000 | 1.1743 | 0.5342 | 0.5399 | 0.5531 | 0.5342 | |
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| 0.6538 | 5.0 | 12500 | 1.2436 | 0.5422 | 0.5435 | 0.5452 | 0.5422 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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