Multilingual-MiniLM-L12-H384-finetunned-elementos-contractuales
This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3775
- Accuracy: 0.9191
- F1: 0.8991
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 23 | 0.9210 | 0.7353 | 0.6231 |
No log | 2.0 | 46 | 0.7792 | 0.7353 | 0.6231 |
No log | 3.0 | 69 | 0.7253 | 0.7059 | 0.6319 |
No log | 4.0 | 92 | 0.5066 | 0.9162 | 0.8966 |
No log | 5.0 | 115 | 0.4528 | 0.9191 | 0.8993 |
No log | 6.0 | 138 | 0.4201 | 0.9221 | 0.9021 |
No log | 7.0 | 161 | 0.4033 | 0.9206 | 0.9013 |
No log | 8.0 | 184 | 0.3979 | 0.9132 | 0.8928 |
No log | 9.0 | 207 | 0.3777 | 0.9221 | 0.9027 |
No log | 10.0 | 230 | 0.3775 | 0.9191 | 0.8991 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
microsoft/Multilingual-MiniLM-L12-H384