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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_V4 |
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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_V4 |
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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: 1.2854 |
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- Map@3: 0.5483 |
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- Accuracy: 0.435 |
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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: 0.2 |
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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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| 1.2365 | 0.11 | 100 | 1.0631 | 0.7583 | 0.64 | |
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| 0.8608 | 0.21 | 200 | 0.7329 | 0.8383 | 0.75 | |
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| 0.8527 | 0.32 | 300 | 0.6985 | 0.8575 | 0.78 | |
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| 0.744 | 0.43 | 400 | 0.6498 | 0.8625 | 0.785 | |
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| 0.7686 | 0.53 | 500 | 0.7450 | 0.8575 | 0.765 | |
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| 1.4098 | 0.64 | 600 | 1.3030 | 0.5575 | 0.4 | |
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| 1.4246 | 0.75 | 700 | 1.3018 | 0.5575 | 0.435 | |
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| 1.3987 | 0.85 | 800 | 1.2906 | 0.5450 | 0.41 | |
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| 1.4121 | 0.96 | 900 | 1.2854 | 0.5483 | 0.435 | |
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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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