---
base_model: griffin-1024-llama3t-8layer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: griffin-1024-llama3t-8layer-simple_wikipedia_LM-vN
  results: []
license: apache-2.0
datasets:
- pszemraj/simple_wikipedia_LM
---

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# griffin-1024-llama3t-8layer-simple_wikipedia_LM-vN

pretraining experiment on the pszemraj/simple_wikipedia_LM dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3584
- Accuracy: 0.3789

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 80085
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 13.6044       | 0.2495 | 100  | 12.5441         | 0.0079   |
| 8.9524        | 0.4989 | 200  | 8.4254          | 0.0473   |
| 7.1721        | 0.7484 | 300  | 6.6199          | 0.0389   |
| 6.2087        | 0.9978 | 400  | 5.7198          | 0.2251   |
| 5.4917        | 1.2473 | 500  | 4.9480          | 0.3268   |
| 4.9408        | 1.4967 | 600  | 4.6730          | 0.3567   |
| 4.8347        | 1.7462 | 700  | 4.4984          | 0.3707   |
| 4.7023        | 1.9956 | 800  | 4.3584          | 0.3789   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1