metadata
base_model: hfl/chinese-roberta-wwm-ext
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: chinese-roberta-climate-related-prediction-V3
results: []
chinese-roberta-climate-related-prediction-V3
This model is a fine-tuned version of hfl/chinese-roberta-wwm-ext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3023
- 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 | 175 | 0.5317 | 0.94 |
No log | 2.0 | 350 | 0.2234 | 0.98 |
0.0124 | 3.0 | 525 | 0.1453 | 0.98 |
0.0124 | 4.0 | 700 | 0.2038 | 0.98 |
0.0124 | 5.0 | 875 | 0.2138 | 0.98 |
0.004 | 6.0 | 1050 | 0.5196 | 0.93 |
0.004 | 7.0 | 1225 | 0.3090 | 0.95 |
0.004 | 8.0 | 1400 | 0.3080 | 0.96 |
0.0033 | 9.0 | 1575 | 0.3067 | 0.96 |
0.0033 | 10.0 | 1750 | 0.3023 | 0.96 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1