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--- |
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license: apache-2.0 |
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base_model: distilbert-base-multilingual-cased |
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tags: |
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- pytorch |
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- amazon-rating |
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- DistilBERTForSequenceClassification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- matthews_correlation |
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model-index: |
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- name: distilbert-base-amazon-multi |
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results: [] |
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datasets: |
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- mteb/amazon_reviews_multi |
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language: |
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- en |
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- de |
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- es |
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- fr |
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- ja |
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- zh |
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library_name: transformers |
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pipeline_tag: text-classification |
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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-amazon-multi |
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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 mteb/amazon_reviews_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9292 |
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- Accuracy: 0.6055 |
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- Matthews Correlation: 0.5072 |
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## Training procedure |
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This model was fine tuned on Google Colab using a single **NVIDIA V100** GPU with 16GB of VRAM. It took around 13 hours to finish the finetuning of 10_000 steps. |
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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: 32 |
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- eval_batch_size: 320 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 100000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Matthews Correlation | |
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|:-------------:|:-----:|:------:|:---------------:|:--------:|:--------------------:| |
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| 1.0008 | 0.26 | 10000 | 1.0027 | 0.5616 | 0.4520 | |
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| 0.9545 | 0.51 | 20000 | 0.9705 | 0.5810 | 0.4788 | |
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| 0.9216 | 0.77 | 30000 | 0.9415 | 0.5883 | 0.4868 | |
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| 0.8765 | 1.03 | 40000 | 0.9495 | 0.5891 | 0.4871 | |
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| 0.8837 | 1.28 | 50000 | 0.9254 | 0.5992 | 0.4997 | |
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| 0.8753 | 1.54 | 60000 | 0.9199 | 0.6014 | 0.5029 | |
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| 0.8572 | 1.8 | 70000 | 0.9108 | 0.6090 | 0.5117 | |
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| 0.7851 | 2.05 | 80000 | 0.9276 | 0.6052 | 0.5066 | |
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| 0.7918 | 2.31 | 90000 | 0.9292 | 0.6055 | 0.5072 | |
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| 0.793 | 2.57 | 100000 | 0.9288 | 0.6064 | 0.5084 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
