16_class_esg-tweet-bert_0909_testing_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: 0.5816
- Accuracy: 0.8537
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: 1e-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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 246 | 1.5902 | 0.4259 |
| No log | 2.0 | 492 | 1.0691 | 0.6548 |
| 1.5573 | 3.0 | 738 | 0.9085 | 0.7223 |
| 1.5573 | 4.0 | 984 | 0.8289 | 0.7392 |
| 0.651 | 5.0 | 1230 | 0.6686 | 0.8143 |
| 0.651 | 6.0 | 1476 | 0.6554 | 0.8293 |
| 0.3968 | 7.0 | 1722 | 0.6103 | 0.8349 |
| 0.3968 | 8.0 | 1968 | 0.5816 | 0.8537 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
google-bert/bert-base-multilingual-cased