metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: haspeech_ita
results: []
haspeech_ita
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1077
- Accuracy: 0.9837
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: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6174 | 0.72 | 100 | 0.5599 | 0.7425 |
| 0.5737 | 1.44 | 200 | 0.4727 | 0.7886 |
| 0.4188 | 2.16 | 300 | 0.3844 | 0.8482 |
| 0.2411 | 2.88 | 400 | 0.1425 | 0.9566 |
| 0.1376 | 3.6 | 500 | 0.1483 | 0.9566 |
| 0.1045 | 4.32 | 600 | 0.1069 | 0.9783 |
| 0.0485 | 5.04 | 700 | 0.1390 | 0.9783 |
| 0.0217 | 5.76 | 800 | 0.0962 | 0.9864 |
| 0.0137 | 6.47 | 900 | 0.0788 | 0.9892 |
| 0.0049 | 7.19 | 1000 | 0.1223 | 0.9810 |
| 0.0043 | 7.91 | 1100 | 0.1077 | 0.9837 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0