metadata
license: mit
base_model: thenlper/gte-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Classify-model-v1.2
results: []
Classify-model-v1.2
This model is a fine-tuned version of thenlper/gte-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3536
- Accuracy: 0.9107
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: 9.5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3025 | 1.0 | 11 | 0.7724 | 0.7411 |
| 0.5536 | 2.0 | 22 | 0.4194 | 0.9018 |
| 0.2468 | 3.0 | 33 | 0.4068 | 0.875 |
| 0.111 | 4.0 | 44 | 0.3455 | 0.8839 |
| 0.0531 | 5.0 | 55 | 0.3453 | 0.8929 |
| 0.0305 | 6.0 | 66 | 0.3536 | 0.9107 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2