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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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- f1
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model-index:
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- name: roberta_crypto_profiling_task1_deberta
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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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# roberta_crypto_profiling_task1_deberta
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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: 2.4722
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- Accuracy: 0.5176
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- F1: 0.4814
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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: 4
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- eval_batch_size: 4
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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 | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 211 | 0.9966 | 0.5882 | 0.5030 |
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| No log | 2.0 | 422 | 1.7145 | 0.5647 | 0.5360 |
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| 0.5073 | 3.0 | 633 | 2.2226 | 0.5176 | 0.4695 |
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| 0.5073 | 4.0 | 844 | 2.1071 | 0.5647 | 0.5222 |
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| 0.112 | 5.0 | 1055 | 2.4722 | 0.5176 | 0.4814 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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