metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: lifechart-bert-base-classifier-hptuning
results: []
lifechart-bert-base-classifier-hptuning
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8018
- Macro F1: 0.7701
- Precision: 0.7496
- Recall: 0.8020
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: 3.189891002979603e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.19371368369975006
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 2.0456 | 1.0 | 821 | 0.9006 | 0.7267 | 0.6845 | 0.7944 |
| 0.6691 | 2.0 | 1642 | 0.8018 | 0.7701 | 0.7496 | 0.8020 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4