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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: DL_Audio_Hatespeech_text_classification_trainer_push |
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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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# DL_Audio_Hatespeech_text_classification_trainer_push |
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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: 1.6725 |
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- Accuracy: 0.7641 |
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- Recall: 0.7771 |
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- Precision: 0.7620 |
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- F1: 0.7695 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 10 |
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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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| 0.0191 | 1.0 | 97 | 1.5765 | 0.7483 | 0.8032 | 0.7281 | 0.7638 | |
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| 0.0351 | 2.0 | 194 | 1.2599 | 0.7428 | 0.8070 | 0.7195 | 0.7607 | |
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| 0.0451 | 3.0 | 291 | 1.1736 | 0.7580 | 0.7860 | 0.7488 | 0.7669 | |
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| 0.039 | 4.0 | 388 | 1.2600 | 0.7557 | 0.7592 | 0.7588 | 0.7590 | |
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| 0.039 | 5.0 | 485 | 1.1336 | 0.7606 | 0.7631 | 0.7640 | 0.7635 | |
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| 0.0199 | 6.0 | 582 | 1.4645 | 0.7593 | 0.7777 | 0.7546 | 0.7660 | |
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| 0.017 | 7.0 | 679 | 1.5825 | 0.7628 | 0.7096 | 0.7997 | 0.7519 | |
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| 0.0062 | 8.0 | 776 | 1.5688 | 0.7673 | 0.7510 | 0.7813 | 0.7658 | |
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| 0.0121 | 9.0 | 873 | 1.6285 | 0.7651 | 0.7510 | 0.7777 | 0.7641 | |
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| 0.0054 | 10.0 | 970 | 1.6725 | 0.7641 | 0.7771 | 0.7620 | 0.7695 | |
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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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