esg-classification_bert_all_data_0509
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: 0.1536
- Accuracy: 0.9643
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 69 | 1.4243 | 0.6245 |
| No log | 2.0 | 138 | 0.6974 | 0.7995 |
| No log | 3.0 | 207 | 0.3928 | 0.8965 |
| No log | 4.0 | 276 | 0.2440 | 0.9441 |
| No log | 5.0 | 345 | 0.1760 | 0.9606 |
| No log | 6.0 | 414 | 0.1536 | 0.9643 |
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-class_bert_all_data_update_preprocess_0509
Base model
google-bert/bert-base-multilingual-cased