metadata
library_name: transformers
license: apache-2.0
base_model: Alibaba-NLP/gte-multilingual-reranker-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ModernBERT-Letter
results: []
ModernBERT-Letter
This model is a fine-tuned version of Alibaba-NLP/gte-multilingual-reranker-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0038
- Accuracy: 1.0
- F1: 1.0
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: 3e-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 161 | 0.4207 | 0.9580 | 0.9554 |
| No log | 2.0 | 322 | 0.0516 | 0.9965 | 0.9964 |
| No log | 3.0 | 483 | 0.0187 | 1.0 | 1.0 |
| 0.391 | 4.0 | 644 | 0.0104 | 1.0 | 1.0 |
| 0.391 | 5.0 | 805 | 0.0072 | 1.0 | 1.0 |
| 0.391 | 6.0 | 966 | 0.0056 | 1.0 | 1.0 |
| 0.0145 | 7.0 | 1127 | 0.0047 | 1.0 | 1.0 |
| 0.0145 | 8.0 | 1288 | 0.0042 | 1.0 | 1.0 |
| 0.0145 | 9.0 | 1449 | 0.0039 | 1.0 | 1.0 |
| 0.0079 | 10.0 | 1610 | 0.0038 | 1.0 | 1.0 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0