adl_hw1_qa_model_bert
This model is a fine-tuned version of hfl/chinese-bert-wwm-ext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7246
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: 3e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 192
- 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 |
|---|---|---|---|
| No log | 0.9956 | 113 | 0.8639 |
| No log | 2.0 | 227 | 0.7221 |
| No log | 2.9868 | 339 | 0.7246 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Downloads last month
- 4
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for b09501048/adl_hw1_qa_model_bert
Base model
hfl/chinese-bert-wwm-ext