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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- recall |
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- precision |
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- f1 |
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model-index: |
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- name: finetuned_text_class |
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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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# finetuned_text_class |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4994 |
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- Accuracy: 0.7702 |
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- Recall: 0.8076 |
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- Precision: 0.7557 |
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- F1: 0.7808 |
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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: 8e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.499 | 0.9961 | 193 | 0.4700 | 0.7602 | 0.7599 | 0.7652 | 0.7625 | |
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| 0.3852 | 1.9974 | 387 | 0.4994 | 0.7702 | 0.8076 | 0.7557 | 0.7808 | |
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| 0.1778 | 2.9987 | 581 | 0.6317 | 0.7638 | 0.6688 | 0.8320 | 0.7415 | |
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| 0.1007 | 4.0 | 775 | 0.8801 | 0.7609 | 0.7662 | 0.7628 | 0.7645 | |
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| 0.0567 | 4.9806 | 965 | 1.0289 | 0.7657 | 0.7586 | 0.7744 | 0.7664 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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