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---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |