---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: albert-base-v2
model-index:
- name: NLI-Lora-Fine-Tuning-10K
  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. -->

# NLI-Lora-Fine-Tuning-10K

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8405
- Accuracy: 0.6071

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 312  | 1.0533          | 0.4667   |
| 1.0642        | 2.0   | 624  | 1.0234          | 0.5033   |
| 1.0642        | 3.0   | 936  | 0.9616          | 0.5467   |
| 1.0052        | 4.0   | 1248 | 0.9010          | 0.5795   |
| 0.9162        | 5.0   | 1560 | 0.8750          | 0.5876   |
| 0.9162        | 6.0   | 1872 | 0.8606          | 0.5959   |
| 0.8817        | 7.0   | 2184 | 0.8512          | 0.6019   |
| 0.8817        | 8.0   | 2496 | 0.8452          | 0.6051   |
| 0.8618        | 9.0   | 2808 | 0.8416          | 0.6071   |
| 0.8551        | 10.0  | 3120 | 0.8405          | 0.6071   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2