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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: 0.4881 |
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- Precision: 0.7966 |
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- Recall: 0.9216 |
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- F1 and accuracy: {'accuracy': 0.7605985037406484, 'f1': 0.8545454545454545} |
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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: 1e-05 |
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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 | 401 | 0.5429 | 0.7631 | 1.0 | {'accuracy': 0.7630922693266833, 'f1': 0.8656294200848657} | |
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| 0.5808 | 2.0 | 802 | 0.5361 | 0.7631 | 1.0 | {'accuracy': 0.7630922693266833, 'f1': 0.8656294200848657} | |
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| 0.5805 | 3.0 | 1203 | 0.5235 | 0.7631 | 1.0 | {'accuracy': 0.7630922693266833, 'f1': 0.8656294200848657} | |
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| 0.5554 | 4.0 | 1604 | 0.5096 | 0.7669 | 1.0 | {'accuracy': 0.7680798004987531, 'f1': 0.8680851063829788} | |
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| 0.5214 | 5.0 | 2005 | 0.5046 | 0.7734 | 0.9706 | {'accuracy': 0.7605985037406484, 'f1': 0.8608695652173913} | |
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| 0.5214 | 6.0 | 2406 | 0.4971 | 0.7950 | 0.9379 | {'accuracy': 0.7680798004987531, 'f1': 0.8605697151424289} | |
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| 0.5152 | 7.0 | 2807 | 0.4919 | 0.7983 | 0.9183 | {'accuracy': 0.7605985037406484, 'f1': 0.8541033434650457} | |
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| 0.4956 | 8.0 | 3208 | 0.4881 | 0.8017 | 0.9118 | {'accuracy': 0.7605985037406484, 'f1': 0.8532110091743118} | |
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| 0.4891 | 9.0 | 3609 | 0.4881 | 0.7972 | 0.9248 | {'accuracy': 0.7630922693266833, 'f1': 0.8562783661119516} | |
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| 0.5038 | 10.0 | 4010 | 0.4881 | 0.7966 | 0.9216 | {'accuracy': 0.7605985037406484, 'f1': 0.8545454545454545} | |
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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 0.15.2 |
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