metadata
base_model: hfl/chinese-macbert-base
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: chinese-macbert-base-climate-transition-physical-risk-prediction-1
results: []
chinese-macbert-base-climate-transition-physical-risk-prediction-1
This model is a fine-tuned version of hfl/chinese-macbert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2265
- Accuracy: 0.96
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 57 | 0.4082 | 0.9 |
No log | 2.0 | 114 | 0.2136 | 0.96 |
No log | 3.0 | 171 | 0.1489 | 0.96 |
No log | 4.0 | 228 | 0.2502 | 0.96 |
No log | 5.0 | 285 | 0.2322 | 0.96 |
No log | 6.0 | 342 | 0.2159 | 0.96 |
No log | 7.0 | 399 | 0.2187 | 0.96 |
No log | 8.0 | 456 | 0.2243 | 0.96 |
0.0464 | 9.0 | 513 | 0.2266 | 0.96 |
0.0464 | 10.0 | 570 | 0.2265 | 0.96 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1