---
base_model: albert/albert-xxlarge-v2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: albert-xxlarge-v2-Adapters_2
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/uwrexp6u)
# albert-xxlarge-v2-Adapters_2

This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5145

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1194        | 0.2291 | 50   | 1.1023          |
| 1.0831        | 0.4582 | 100  | 1.0770          |
| 1.0148        | 0.6873 | 150  | 0.9637          |
| 0.9064        | 0.9164 | 200  | 0.8538          |
| 0.7693        | 1.1455 | 250  | 0.7700          |
| 0.7445        | 1.3746 | 300  | 0.7098          |
| 0.7045        | 1.6037 | 350  | 0.6914          |
| 0.6733        | 1.8328 | 400  | 0.6374          |
| 0.6239        | 2.0619 | 450  | 0.6226          |
| 0.6208        | 2.2910 | 500  | 0.5913          |
| 0.6153        | 2.5200 | 550  | 0.5811          |
| 0.591         | 2.7491 | 600  | 0.5630          |
| 0.5894        | 2.9782 | 650  | 0.5500          |
| 0.5788        | 3.2073 | 700  | 0.5461          |
| 0.5187        | 3.4364 | 750  | 0.5353          |
| 0.5271        | 3.6655 | 800  | 0.5386          |
| 0.5812        | 3.8946 | 850  | 0.5309          |
| 0.5532        | 4.1237 | 900  | 0.5296          |
| 0.5602        | 4.3528 | 950  | 0.5204          |
| 0.5209        | 4.5819 | 1000 | 0.5144          |
| 0.5579        | 4.8110 | 1050 | 0.5145          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.1.0
- Datasets 2.20.0
- Tokenizers 0.19.1