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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: 0.5734 |
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- Precision: 0.7362 |
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- Recall: 0.8026 |
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- F1 and accuracy: {'accuracy': 0.6970509383378016, 'f1': 0.7679671457905544} |
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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 | 372 | 0.6573 | 0.6247 | 1.0 | {'accuracy': 0.6246648793565683, 'f1': 0.768976897689769} | |
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| 0.6699 | 2.0 | 744 | 0.6452 | 0.6247 | 1.0 | {'accuracy': 0.6246648793565683, 'f1': 0.768976897689769} | |
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| 0.6412 | 3.0 | 1116 | 0.6130 | 0.6602 | 0.8755 | {'accuracy': 0.6407506702412868, 'f1': 0.7527675276752768} | |
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| 0.6412 | 4.0 | 1488 | 0.5949 | 0.7413 | 0.8240 | {'accuracy': 0.710455764075067, 'f1': 0.7804878048780487} | |
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| 0.6158 | 5.0 | 1860 | 0.5860 | 0.7323 | 0.8455 | {'accuracy': 0.710455764075067, 'f1': 0.7848605577689244} | |
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| 0.5891 | 6.0 | 2232 | 0.5802 | 0.7381 | 0.7983 | {'accuracy': 0.6970509383378016, 'f1': 0.7670103092783506} | |
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| 0.5855 | 7.0 | 2604 | 0.5770 | 0.7354 | 0.8112 | {'accuracy': 0.6997319034852547, 'f1': 0.7714285714285714} | |
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| 0.5855 | 8.0 | 2976 | 0.5757 | 0.7328 | 0.8240 | {'accuracy': 0.7024128686327078, 'f1': 0.7757575757575758} | |
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| 0.5839 | 9.0 | 3348 | 0.5741 | 0.7362 | 0.8026 | {'accuracy': 0.6970509383378016, 'f1': 0.7679671457905544} | |
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| 0.5759 | 10.0 | 3720 | 0.5734 | 0.7362 | 0.8026 | {'accuracy': 0.6970509383378016, 'f1': 0.7679671457905544} | |
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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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