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--- |
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license: mit |
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base_model: microsoft/deberta-v3-base |
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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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- f1 |
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- accuracy |
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model-index: |
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- name: deberta-v3-base-Whatsapp-ner |
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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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# deberta-v3-base-Whatsapp-ner |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0904 |
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- Precision: 0.9322 |
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- Recall: 0.9649 |
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- F1: 0.9483 |
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- Accuracy: 0.9813 |
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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: 0.0002 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 58 | 0.1103 | 0.9316 | 0.9561 | 0.9437 | 0.9762 | |
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| No log | 2.0 | 116 | 0.1157 | 0.9474 | 0.9474 | 0.9474 | 0.9796 | |
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| No log | 3.0 | 174 | 0.1069 | 0.9153 | 0.9474 | 0.9310 | 0.9779 | |
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| No log | 4.0 | 232 | 0.0904 | 0.9322 | 0.9649 | 0.9483 | 0.9813 | |
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| No log | 5.0 | 290 | 0.0990 | 0.9322 | 0.9649 | 0.9483 | 0.9796 | |
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| No log | 6.0 | 348 | 0.0964 | 0.9244 | 0.9649 | 0.9442 | 0.9813 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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