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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: My_Model |
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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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# My_Model |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4353 |
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- Accuracy@en: 0.8946 |
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- F1@en: 0.8931 |
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- Precision@en: 0.8965 |
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- Recall@en: 0.8952 |
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- Loss@en: 0.4353 |
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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: 8 |
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- eval_batch_size: 8 |
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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 | Accuracy@en | F1@en | Precision@en | Recall@en | Loss@en | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|:------------:|:---------:|:-------:| |
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| 3.1352 | 1.0 | 700 | 2.5257 | 0.3279 | 0.2574 | 0.3241 | 0.3350 | 2.5257 | |
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| 2.1929 | 2.0 | 1400 | 1.6830 | 0.6121 | 0.5597 | 0.6589 | 0.6125 | 1.6830 | |
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| 1.4355 | 3.0 | 2100 | 1.0143 | 0.7929 | 0.7750 | 0.7990 | 0.7914 | 1.0143 | |
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| 0.9043 | 4.0 | 2800 | 0.6990 | 0.8242 | 0.8062 | 0.8239 | 0.8248 | 0.6990 | |
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| 0.6269 | 5.0 | 3500 | 0.5446 | 0.8796 | 0.8783 | 0.8845 | 0.8802 | 0.5446 | |
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| 0.4852 | 6.0 | 4200 | 0.4860 | 0.8862 | 0.8847 | 0.8901 | 0.8862 | 0.4860 | |
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| 0.4124 | 7.0 | 4900 | 0.4538 | 0.8892 | 0.8876 | 0.8925 | 0.8896 | 0.4538 | |
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| 0.3602 | 8.0 | 5600 | 0.4392 | 0.89 | 0.8886 | 0.8925 | 0.8906 | 0.4392 | |
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| 0.3355 | 9.0 | 6300 | 0.4373 | 0.8912 | 0.8898 | 0.8934 | 0.8919 | 0.4373 | |
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| 0.3147 | 10.0 | 7000 | 0.4353 | 0.8946 | 0.8931 | 0.8965 | 0.8952 | 0.4353 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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