metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bpeo_classifier
results: []
bpeo_classifier
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: 0.4615
- Accuracy: 0.8522
- F1: 0.8506
- Precision: 0.8536
- Recall: 0.8522
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: 16
- eval_batch_size: 16
- 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 164 | 0.4292 | 0.8247 | 0.8266 | 0.8292 | 0.8247 |
| No log | 2.0 | 328 | 0.4365 | 0.8351 | 0.8314 | 0.8334 | 0.8351 |
| No log | 3.0 | 492 | 0.4568 | 0.8385 | 0.8395 | 0.8416 | 0.8385 |
| 0.2652 | 4.0 | 656 | 0.4615 | 0.8522 | 0.8506 | 0.8536 | 0.8522 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3