---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: albert/albert-base-v2
model-index:
- name: NLI-Lora-Fine-Tuning-10K-ALBERTA
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NLI-Lora-Fine-Tuning-10K-ALBERTA

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co./albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8439
- Accuracy: 0.6063

## 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  | 1.0562          | 0.4551   |
| 1.0762        | 2.0   | 624  | 1.0236          | 0.4995   |
| 1.0762        | 3.0   | 936  | 0.9603          | 0.5361   |
| 1.0075        | 4.0   | 1248 | 0.9053          | 0.5671   |
| 0.9178        | 5.0   | 1560 | 0.8796          | 0.5823   |
| 0.9178        | 6.0   | 1872 | 0.8649          | 0.5934   |
| 0.8859        | 7.0   | 2184 | 0.8551          | 0.5977   |
| 0.8859        | 8.0   | 2496 | 0.8488          | 0.6033   |
| 0.8632        | 9.0   | 2808 | 0.8450          | 0.6057   |
| 0.8543        | 10.0  | 3120 | 0.8439          | 0.6063   |


### Framework versions

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