metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: dress-classifier
results: []
dress-classifier
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- F1: 0.9260
- Loss: 0.3490
- Accuracy: 0.9256
- Precision: 0.9265
- Recall: 0.9256
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: 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 | F1 | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 269 | 0.8817 | 0.2965 | 0.8940 | 0.8942 | 0.8940 |
| 0.3442 | 2.0 | 538 | 0.9133 | 0.2740 | 0.9163 | 0.9133 | 0.9163 |
| 0.3442 | 3.0 | 807 | 0.9096 | 0.2904 | 0.9060 | 0.9174 | 0.9060 |
| 0.1397 | 4.0 | 1076 | 0.9231 | 0.3103 | 0.9237 | 0.9227 | 0.9237 |
| 0.1397 | 5.0 | 1345 | 0.9260 | 0.3490 | 0.9256 | 0.9265 | 0.9256 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1