---
library_name: transformers
license: apache-2.0
base_model: cross-encoder/nli-deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: enli-deberta-v3-large_10
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# enli-deberta-v3-large_10

This model is a fine-tuned version of [cross-encoder/nli-deberta-v3-large](https://huggingface.co/cross-encoder/nli-deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8908
- Accuracy: 0.9083
- F1: 0.9088

## 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: 16
- eval_batch_size: 16
- 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: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.2817        | 1.0   | 3516  | 0.2948          | 0.9042   | 0.9045 |
| 0.1676        | 2.0   | 7032  | 0.3862          | 0.9029   | 0.9033 |
| 0.1199        | 3.0   | 10548 | 0.5174          | 0.9017   | 0.9021 |
| 0.0501        | 4.0   | 14064 | 0.6014          | 0.9039   | 0.9043 |
| 0.0489        | 5.0   | 17580 | 0.7007          | 0.9034   | 0.9039 |
| 0.0173        | 6.0   | 21096 | 0.7448          | 0.9049   | 0.9056 |
| 0.0142        | 7.0   | 24612 | 0.7086          | 0.9062   | 0.9068 |
| 0.0003        | 8.0   | 28128 | 0.8314          | 0.9074   | 0.9079 |
| 0.0059        | 9.0   | 31644 | 0.8942          | 0.9078   | 0.9083 |
| 0.0           | 10.0  | 35160 | 0.8908          | 0.9083   | 0.9088 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1