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--- |
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license: mit |
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base_model: microsoft/deberta-v3-large |
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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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model-index: |
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- name: checkpoints_28_9_microsoft_deberta_V2 |
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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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# checkpoints_28_9_microsoft_deberta_V2 |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5675 |
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- Map@3: 0.8842 |
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- Accuracy: 0.815 |
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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: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Map@3 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
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| 1.0011 | 0.11 | 100 | 0.8842 | 0.8258 | 0.74 | |
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| 0.8398 | 0.21 | 200 | 0.6978 | 0.8667 | 0.79 | |
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| 0.8414 | 0.32 | 300 | 0.6337 | 0.8625 | 0.795 | |
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| 0.7461 | 0.43 | 400 | 0.6609 | 0.8600 | 0.775 | |
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| 0.7131 | 0.53 | 500 | 0.6329 | 0.8758 | 0.805 | |
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| 0.6891 | 0.64 | 600 | 0.6157 | 0.8892 | 0.83 | |
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| 0.6969 | 0.75 | 700 | 0.5917 | 0.8808 | 0.805 | |
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| 0.6775 | 0.85 | 800 | 0.5698 | 0.8817 | 0.81 | |
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| 0.6534 | 0.96 | 900 | 0.5675 | 0.8842 | 0.815 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.3 |
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