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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: distilbert-base-multilingual-cased-lora-text-classification |
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results: [] |
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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-lora-text-classification |
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5714 |
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- Precision: 0.7417 |
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- Recall: 1.0 |
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- F1 and accuracy: {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} |
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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: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 and accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:----------------------------------------------------------:| |
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| No log | 1.0 | 391 | 0.5780 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.647 | 2.0 | 782 | 0.5748 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6216 | 3.0 | 1173 | 0.5713 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6201 | 4.0 | 1564 | 0.5726 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6201 | 5.0 | 1955 | 0.5765 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6199 | 6.0 | 2346 | 0.5756 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6365 | 7.0 | 2737 | 0.5827 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6165 | 8.0 | 3128 | 0.5715 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6185 | 9.0 | 3519 | 0.5715 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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| 0.6185 | 10.0 | 3910 | 0.5714 | 0.7417 | 1.0 | {'accuracy': 0.7416879795396419, 'f1': 0.8516886930983847} | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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