metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: original_model_fast_2
results: []
original_model_fast_2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5424
- Accuracy: 0.5282
- F1: 0.5311
- Precision: 0.5429
- Recall: 0.5280
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: 3e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3323 | 0.1566 | 500 | 0.8817 | 0.7273 | 0.7080 | 0.7290 | 0.7142 |
| 0.2778 | 0.3132 | 1000 | 0.8832 | 0.7286 | 0.7159 | 0.7264 | 0.7184 |
| 0.2965 | 0.4698 | 1500 | 0.8859 | 0.7242 | 0.7086 | 0.7216 | 0.7127 |
| 0.2977 | 0.6264 | 2000 | 0.8766 | 0.7247 | 0.7100 | 0.7236 | 0.7135 |
| 0.3062 | 0.7830 | 2500 | 0.8881 | 0.7242 | 0.7102 | 0.7246 | 0.7134 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1