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Uploading crypto fundamental news classifier model
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metadata
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: []

crypto_fundamental_news_text_classifier-distilbert-base-uncased

This model is a fine-tuned version of 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