metadata
tags:
- generated_from_trainer
metrics:
- accuracy
license: apache-2.0
datasets:
- pszemraj/simple_wikipedia_LM
language:
- en
griffin-v0.01-c3t-8layer-simplewiki-silu
- griffin/recurrent_gemma arch
- claude3 tokenizer (as an HF gpt2 tokenizer)
Model description
pretrain experiment on the pszemraj/simple_wikipedia_LM dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0476
- Accuracy: 0.4224
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 |
|---|---|---|---|---|
| 13.3276 | 0.2548 | 100 | 12.0402 | 0.0131 |
| 8.9207 | 0.5095 | 200 | 8.0312 | 0.0360 |
| 7.2681 | 0.7643 | 300 | 6.4775 | 0.0506 |
| 6.3187 | 1.0190 | 400 | 5.6227 | 0.0434 |
| 5.5695 | 1.2738 | 500 | 4.7796 | 0.3635 |
| 5.2926 | 1.5285 | 600 | 4.3923 | 0.3952 |
| 4.878 | 1.7833 | 700 | 4.1877 | 0.4085 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1