metadata
license: mit
base_model: intfloat/multilingual-e5-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: digidawfinal2
results: []
digidawfinal2
This model is a fine-tuned version of intfloat/multilingual-e5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6325
- Accuracy: 0.826
- Precision: 0.4849
- Recall: 0.3920
- F1: 0.4038
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: 0.0001
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.3648 | 1.0 | 157 | 0.7544 | 0.8 | 0.1481 | 0.1495 | 0.1451 |
| 1.0523 | 2.0 | 314 | 0.7241 | 0.791 | 0.3328 | 0.3616 | 0.3064 |
| 0.8635 | 3.0 | 471 | 0.6325 | 0.826 | 0.4849 | 0.3920 | 0.4038 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1