metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-ia-checkpoint
results: []
bert-ia-checkpoint
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7216
- Accuracy: 0.7229
- F1 Macro: 0.6963
- Precision Macro: 0.7200
- Recall Macro: 0.6916
- Auc: 0.7626
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 0.6736 | 0.7261 | 0.7028 | 0.7210 | 0.6981 | 0.7428 |
| No log | 2.0 | 158 | 0.8024 | 0.7006 | 0.6975 | 0.6995 | 0.7070 | 0.7566 |
| No log | 3.0 | 237 | 0.9896 | 0.7389 | 0.7226 | 0.7307 | 0.7189 | 0.7613 |
| No log | 4.0 | 316 | 1.3463 | 0.7229 | 0.7032 | 0.7145 | 0.6992 | 0.7444 |
| No log | 5.0 | 395 | 1.4706 | 0.7357 | 0.7246 | 0.7256 | 0.7238 | 0.7536 |
| No log | 6.0 | 474 | 1.6432 | 0.7420 | 0.7264 | 0.7339 | 0.7228 | 0.7518 |
| 0.176 | 7.0 | 553 | 1.7216 | 0.7229 | 0.6963 | 0.7200 | 0.6916 | 0.7626 |
| 0.176 | 8.0 | 632 | 1.7837 | 0.7357 | 0.7078 | 0.7383 | 0.7023 | 0.7596 |
| 0.176 | 9.0 | 711 | 1.7627 | 0.7325 | 0.7129 | 0.7256 | 0.7085 | 0.7611 |
| 0.176 | 10.0 | 790 | 1.7560 | 0.7357 | 0.7188 | 0.7275 | 0.7149 | 0.7610 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1