---
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-cased-lora-1.58M-snli-model2
  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. -->

# bert-large-cased-lora-1.58M-snli-model2

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co./bert-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8331
- Accuracy: 0.687

## 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: 256
- eval_batch_size: 256
- seed: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5164        | 1.0   | 2146 | 0.4262          | 0.8406   |
| 0.4687        | 2.0   | 4292 | 0.3904          | 0.8540   |
| 0.4562        | 3.0   | 6438 | 0.3824          | 0.8575   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0