metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: attr_classification
results: []
attr_classification
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2170
- Precision: 0.9359
- Recall: 0.9574
- F1: 0.9465
- Accuracy: 0.9575
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 139 | 0.2243 | 0.9251 | 0.9311 | 0.9281 | 0.9475 |
| No log | 2.0 | 278 | 0.2090 | 0.9268 | 0.9541 | 0.9402 | 0.9525 |
| No log | 3.0 | 417 | 0.2170 | 0.9359 | 0.9574 | 0.9465 | 0.9575 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1