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update model card README.md
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README.md
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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-targin-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-targin-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: 0.6266
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- Accuracy: 0.6996
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- Precision: 0.6665
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- Recall: 0.6760
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- F1: 0.6698
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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 | 0.5638 | 0.6749 | 0.6505 | 0.6657 | 0.6523 |
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| 0.5784 | 2.0 | 592 | 0.5621 | 0.7034 | 0.6713 | 0.6818 | 0.6748 |
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| 0.5784 | 3.0 | 888 | 0.5802 | 0.7082 | 0.6730 | 0.6794 | 0.6757 |
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| 0.4968 | 4.0 | 1184 | 0.5965 | 0.7110 | 0.6736 | 0.6756 | 0.6746 |
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| 0.4968 | 5.0 | 1480 | 0.6266 | 0.6996 | 0.6665 | 0.6760 | 0.6698 |
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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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