---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta_crypto_profiling_task1_deberta
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta_crypto_profiling_task1_deberta

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4722
- Accuracy: 0.5176
- F1: 0.4814

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 211  | 0.9966          | 0.5882   | 0.5030 |
| No log        | 2.0   | 422  | 1.7145          | 0.5647   | 0.5360 |
| 0.5073        | 3.0   | 633  | 2.2226          | 0.5176   | 0.4695 |
| 0.5073        | 4.0   | 844  | 2.1071          | 0.5647   | 0.5222 |
| 0.112         | 5.0   | 1055 | 2.4722          | 0.5176   | 0.4814 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3