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--- |
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license: mit |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: mdeberta-profane-final |
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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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# mdeberta-profane-final |
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2269 |
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- Accuracy: 0.9154 |
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- Precision: 0.8684 |
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- Recall: 0.8558 |
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- F1: 0.8618 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 296 | 0.2324 | 0.9125 | 0.8672 | 0.8446 | 0.8552 | |
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| 0.3129 | 2.0 | 592 | 0.2081 | 0.9202 | 0.8814 | 0.8549 | 0.8673 | |
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| 0.3129 | 3.0 | 888 | 0.2155 | 0.9183 | 0.8747 | 0.8575 | 0.8657 | |
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| 0.2136 | 4.0 | 1184 | 0.2164 | 0.9154 | 0.8738 | 0.8464 | 0.8591 | |
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| 0.2136 | 5.0 | 1480 | 0.2269 | 0.9154 | 0.8684 | 0.8558 | 0.8618 | |
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### Framework versions |
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- Transformers 4.24.0.dev0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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