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--- |
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license: mit |
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base_model: microsoft/deberta-v3-small |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: deeva-modcat-seqclass-deberta-v1 |
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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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# deeva-modcat-seqclass-deberta-v1 |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6435 |
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- Accuracy: 0.7161 |
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- F1: 0.2922 |
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- Precision: 0.1808 |
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- Recall: 0.7619 |
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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: 2e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 0.18 | 2 | 0.7148 | 0.4139 | 0.0476 | 0.0272 | 0.1905 | |
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| No log | 0.36 | 4 | 0.7027 | 0.4835 | 0.0408 | 0.0238 | 0.1429 | |
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| No log | 0.55 | 6 | 0.6917 | 0.5586 | 0.0474 | 0.0284 | 0.1429 | |
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| No log | 0.73 | 8 | 0.6817 | 0.5604 | 0.0476 | 0.0286 | 0.1429 | |
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| No log | 0.91 | 10 | 0.6727 | 0.5623 | 0.0478 | 0.0287 | 0.1429 | |
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| No log | 1.09 | 12 | 0.6648 | 0.6374 | 0.0571 | 0.0357 | 0.1429 | |
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| No log | 1.27 | 14 | 0.6578 | 0.6374 | 0.0571 | 0.0357 | 0.1429 | |
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| No log | 1.45 | 16 | 0.6521 | 0.6355 | 0.0569 | 0.0355 | 0.1429 | |
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| No log | 1.64 | 18 | 0.6477 | 0.6392 | 0.1005 | 0.0621 | 0.2619 | |
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| No log | 1.82 | 20 | 0.6448 | 0.7015 | 0.2419 | 0.1503 | 0.6190 | |
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| No log | 2.0 | 22 | 0.6435 | 0.7161 | 0.2922 | 0.1808 | 0.7619 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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