metadata
base_model: ElKulako/cryptobert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
results: []
results
This model is a fine-tuned version of ElKulako/cryptobert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8983
- Accuracy: 0.6433
- Precision: 0.6614
- Recall: 0.6433
- F1: 0.6461
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: 3.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 69420
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.9586 | 0.19 | 100 | 0.8746 | 0.6033 | 0.5990 | 0.6033 | 0.5944 |
| 0.7362 | 0.38 | 200 | 0.8187 | 0.63 | 0.6322 | 0.63 | 0.6232 |
| 0.577 | 0.57 | 300 | 0.8065 | 0.6767 | 0.6821 | 0.6767 | 0.6761 |
| 0.4632 | 0.76 | 400 | 0.8437 | 0.63 | 0.6411 | 0.63 | 0.6321 |
| 0.3243 | 0.95 | 500 | 0.8983 | 0.6433 | 0.6614 | 0.6433 | 0.6461 |
| 0.2257 | 1.14 | 600 | 1.3704 | 0.6033 | 0.6863 | 0.6033 | 0.6046 |
| 0.1333 | 1.33 | 700 | 1.2951 | 0.6033 | 0.6201 | 0.6033 | 0.6052 |
| 0.0574 | 1.52 | 800 | 1.5119 | 0.6333 | 0.6331 | 0.6333 | 0.6309 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Tokenizers 0.15.0