metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-chinese
tags:
- generated_from_trainer
model-index:
- name: classification_v4
results: []
classification_v4
This model is a fine-tuned version of bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0438
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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_steps: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 5 | 0.9302 |
| 6.6577 | 2.0 | 10 | 0.6506 |
| 6.6577 | 3.0 | 15 | 0.4304 |
| 3.7074 | 4.0 | 20 | 0.2966 |
| 3.7074 | 5.0 | 25 | 0.2045 |
| 1.8157 | 6.0 | 30 | 0.1249 |
| 1.8157 | 7.0 | 35 | 0.0834 |
| 0.8190 | 8.0 | 40 | 0.0598 |
| 0.8190 | 9.0 | 45 | 0.0478 |
| 0.4603 | 10.0 | 50 | 0.0438 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2