---
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-allagree
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# intfloat-e5-base-v2-english-fp16-allagree

This model is a fine-tuned version of [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1038
- Accuracy: 0.9780
- Precision: 0.9779
- Recall: 0.9780
- F1: 0.9779

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8016        | 3.3448 | 50   | 0.3066          | 0.9339   | 0.9343    | 0.9339 | 0.9325 |
| 0.1009        | 6.6897 | 100  | 0.1038          | 0.9780   | 0.9779    | 0.9780 | 0.9779 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0