---
library_name: transformers
license: apache-2.0
base_model: cross-encoder/nli-MiniLM2-L6-H768
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nli-MiniLM2-L6-H768-answerable-or-not
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# nli-MiniLM2-L6-H768-answerable-or-not

This model is a fine-tuned version of [cross-encoder/nli-MiniLM2-L6-H768](https://huggingface.co/cross-encoder/nli-MiniLM2-L6-H768) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0262
- Accuracy: 0.9949

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1299        | 1.0   | 198  | 0.1615          | 0.9620   |
| 0.1317        | 2.0   | 396  | 0.0953          | 0.9848   |
| 0.0007        | 3.0   | 594  | 0.0952          | 0.9823   |
| 0.0005        | 4.0   | 792  | 0.0404          | 0.9949   |
| 0.0970        | 5.0   | 990  | 0.0598          | 0.9873   |
| 0.1482        | 6.0   | 1188 | 0.0394          | 0.9899   |
| 0.0002        | 7.0   | 1386 | 0.0260          | 0.9949   |
| 0.0002        | 8.0   | 1584 | 0.0796          | 0.9873   |
| 0.0002        | 9.0   | 1782 | 0.0464          | 0.9924   |
| 0.0002        | 10.0  | 1980 | 0.0463          | 0.9924   |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2