esg-classification_bert_all_data_0509_other_v1
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6887
- Accuracy: 0.8153
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 63 | 1.7731 | 0.4217 |
| No log | 2.0 | 126 | 1.0752 | 0.7068 |
| No log | 3.0 | 189 | 0.8234 | 0.7631 |
| No log | 4.0 | 252 | 0.7167 | 0.8112 |
| No log | 5.0 | 315 | 0.6887 | 0.8153 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for dsmsb/esg-classification_bert_all_data_0509_other_v1
Base model
google-bert/bert-base-multilingual-cased