|
--- |
|
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 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# 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 |
