metadata
library_name: transformers
license: mit
base_model: intfloat/e5-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: intfloat-e5-base-v2-english-fp16
results: []
intfloat-e5-base-v2-english-fp16
This model is a fine-tuned version of intfloat/e5-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3221
- Accuracy: 0.8870
- Precision: 0.8870
- Recall: 0.8870
- F1: 0.8857
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.0595 | 0.3922 | 50 | 0.9726 | 0.4848 | 0.6053 | 0.4848 | 0.3207 |
| 0.8926 | 0.7843 | 100 | 0.7673 | 0.6464 | 0.7131 | 0.6464 | 0.5740 |
| 0.6469 | 1.1725 | 150 | 0.5323 | 0.8355 | 0.8342 | 0.8355 | 0.8318 |
| 0.439 | 1.5647 | 200 | 0.4221 | 0.8644 | 0.8670 | 0.8644 | 0.8614 |
| 0.3651 | 1.9569 | 250 | 0.3502 | 0.8703 | 0.8726 | 0.8703 | 0.8674 |
| 0.2839 | 2.3451 | 300 | 0.3221 | 0.8870 | 0.8870 | 0.8870 | 0.8857 |
| 0.2728 | 2.7373 | 350 | 0.3246 | 0.8831 | 0.8834 | 0.8831 | 0.8815 |
| 0.2459 | 3.1255 | 400 | 0.3564 | 0.8787 | 0.8807 | 0.8787 | 0.8768 |
| 0.1875 | 3.5176 | 450 | 0.3339 | 0.8846 | 0.8838 | 0.8846 | 0.8838 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1