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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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- f1 |
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model-index: |
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- name: edos-2023-baseline-microsoft-deberta-v3-base-label_vector |
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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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# edos-2023-baseline-microsoft-deberta-v3-base-label_vector |
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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: 1.5524 |
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- F1: 0.3162 |
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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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- lr_scheduler_warmup_steps: 5 |
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- num_epochs: 12 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.1209 | 1.18 | 100 | 1.9990 | 0.0801 | |
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| 1.7997 | 2.35 | 200 | 1.7293 | 0.1349 | |
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| 1.5749 | 3.53 | 300 | 1.6080 | 0.2431 | |
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| 1.3674 | 4.71 | 400 | 1.5411 | 0.2793 | |
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| 1.2214 | 5.88 | 500 | 1.5285 | 0.2980 | |
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| 1.0752 | 7.06 | 600 | 1.5165 | 0.3054 | |
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| 0.9899 | 8.24 | 700 | 1.5210 | 0.3186 | |
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| 0.8733 | 9.41 | 800 | 1.5385 | 0.3134 | |
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| 0.8578 | 10.59 | 900 | 1.5524 | 0.3162 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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