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library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: db_himp_4.2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# db_himp_4.2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6350
- Accuracy: 0.9290
- F1 Weighted: 0.9284
- F1 Macro: 0.9315
- Precision Weighted: 0.9289
- Recall Weighted: 0.9290
- Precision Macro: 0.9297
- Recall Macro: 0.9339
## 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: 2.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 9
- label_smoothing_factor: 0.05
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Macro | Precision Weighted | Recall Weighted | Precision Macro | Recall Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:------------------:|:---------------:|:---------------:|:------------:|
| 1.3724 | 1.0 | 772 | 1.0129 | 0.8106 | 0.8086 | 0.8082 | 0.8128 | 0.8106 | 0.8117 | 0.8114 |
| 0.8057 | 2.0 | 1544 | 0.7635 | 0.8810 | 0.8796 | 0.8828 | 0.8818 | 0.8810 | 0.8815 | 0.8872 |
| 0.6641 | 3.0 | 2316 | 0.7049 | 0.9038 | 0.9027 | 0.9052 | 0.9038 | 0.9038 | 0.9043 | 0.9081 |
| 0.5781 | 4.0 | 3088 | 0.6703 | 0.9156 | 0.9152 | 0.9181 | 0.9163 | 0.9156 | 0.9181 | 0.9195 |
| 0.5372 | 5.0 | 3860 | 0.6480 | 0.9226 | 0.9219 | 0.9248 | 0.9225 | 0.9226 | 0.9229 | 0.9277 |
| 0.5081 | 6.0 | 4632 | 0.6425 | 0.9253 | 0.9248 | 0.9275 | 0.9256 | 0.9253 | 0.9259 | 0.9300 |
| 0.4850 | 7.0 | 5404 | 0.6362 | 0.9280 | 0.9276 | 0.9305 | 0.9282 | 0.9280 | 0.9297 | 0.9320 |
| 0.4638 | 8.0 | 6176 | 0.6352 | 0.9288 | 0.9283 | 0.9312 | 0.9288 | 0.9288 | 0.9298 | 0.9334 |
| 0.4603 | 9.0 | 6948 | 0.6350 | 0.9290 | 0.9284 | 0.9315 | 0.9289 | 0.9290 | 0.9297 | 0.9339 |
### Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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