distilbert-base-multilingual-cased-finetuned-geordie
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0262
- Precision: 0.9029
- Recall: 0.9162
- F1: 0.9095
- Accuracy: 0.9933
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.022 | 1.0 | 10080 | 0.0205 | 0.8689 | 0.9270 | 0.8970 | 0.9927 |
0.0156 | 2.0 | 20160 | 0.0203 | 0.9034 | 0.9072 | 0.9053 | 0.9930 |
0.0106 | 3.0 | 30240 | 0.0223 | 0.9010 | 0.9157 | 0.9083 | 0.9932 |
0.0082 | 4.0 | 40320 | 0.0262 | 0.9029 | 0.9162 | 0.9095 | 0.9933 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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