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---
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 |