---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: crypto_fundamental_news_text_classifier-distilbert-base-uncased
  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. -->

# crypto_fundamental_news_text_classifier-distilbert-base-uncased

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3716
- Accuracy: 0.9194

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0913        | 1.0   | 8    | 1.1070          | 0.2097   |
| 1.0507        | 2.0   | 16   | 1.0611          | 0.4032   |
| 0.9942        | 3.0   | 24   | 0.9997          | 0.5161   |
| 0.8923        | 4.0   | 32   | 0.9018          | 0.5968   |
| 0.7789        | 5.0   | 40   | 0.8149          | 0.6774   |
| 0.675         | 6.0   | 48   | 0.7557          | 0.7903   |
| 0.6047        | 7.0   | 56   | 0.6935          | 0.7903   |
| 0.5335        | 8.0   | 64   | 0.6468          | 0.8548   |
| 0.4758        | 9.0   | 72   | 0.6036          | 0.8871   |
| 0.43          | 10.0  | 80   | 0.5686          | 0.8871   |
| 0.3939        | 11.0  | 88   | 0.5312          | 0.9032   |
| 0.349         | 12.0  | 96   | 0.4888          | 0.9194   |
| 0.3127        | 13.0  | 104  | 0.4539          | 0.9194   |
| 0.2806        | 14.0  | 112  | 0.4281          | 0.9194   |
| 0.2624        | 15.0  | 120  | 0.4062          | 0.9194   |
| 0.2362        | 16.0  | 128  | 0.3953          | 0.9194   |
| 0.2231        | 17.0  | 136  | 0.3839          | 0.9194   |
| 0.2161        | 18.0  | 144  | 0.3799          | 0.9194   |
| 0.2023        | 19.0  | 152  | 0.3753          | 0.9194   |
| 0.1982        | 20.0  | 160  | 0.3716          | 0.9194   |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.0