Using the ClimateBERT-f model as starting point,the TCFD-BERT language model is additionally pre-trained to include precise paragraphs related to climate change.
TCFD-BERT
It achieves the following results on the evaluation set:
- Loss: 1.1325
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.865 | 0.37 | 500 | 1.4460 |
1.6601 | 0.73 | 1000 | 1.3491 |
1.593 | 1.1 | 1500 | 1.3190 |
1.5336 | 1.46 | 2000 | 1.2801 |
1.5081 | 1.83 | 2500 | 1.2446 |
1.4547 | 2.19 | 3000 | 1.2281 |
1.4358 | 2.56 | 3500 | 1.2065 |
1.4121 | 2.92 | 4000 | 1.1874 |
1.396 | 3.29 | 4500 | 1.1817 |
1.383 | 3.65 | 5000 | 1.1747 |
1.3662 | 4.02 | 5500 | 1.1717 |
1.3545 | 4.38 | 6000 | 1.1567 |
1.3441 | 4.75 | 6500 | 1.1325 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.9.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1
- Downloads last month
- 164