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---
license: apache-2.0
base_model: pszemraj/griffin-v0.01-c3t-8layer-simplewiki-silu
tags:
- generated_from_trainer
metrics:
- accuracy
datasets:
- BEE-spoke-data/fineweb-1M_en-med
language:
- en
---
<!-- 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-c3t-8L-v0.02-fineweb
Pretraining experiment with griffin/recurrent_gemma arch
## Model description
Further training of [pszemraj/griffin-v0.01-c3t-8layer-simplewiki-silu](https://hf.co/pszemraj/griffin-v0.01-c3t-8layer-simplewiki-silu) on the BEE-spoke-data/fineweb-1M_en-med dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1888
- Accuracy: 0.2326
- Num Input Tokens Seen: 798621696
## numbers
tl;dr its bad/would need more training:
hf (pretrained=pszemraj/griffin-c3t-8L-v0.02-fineweb,trust_remote_code=True,dtype=float), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 4
| Tasks |Version|Filter|n-shot| Metric | Value | | Stderr |
|--------------|------:|------|-----:|----------|----------:|---|---------:|
|winogrande | 1|none | 0|acc | 0.5146|± | 0.0140|
|piqa | 1|none | 0|acc | 0.5511|± | 0.0116|
| | |none | 0|acc_norm | 0.5261|± | 0.0116|
|openbookqa | 1|none | 0|acc | 0.1140|± | 0.0142|
| | |none | 0|acc_norm | 0.2240|± | 0.0187|
|lambada_openai| 1|none | 0|perplexity|209503.2246|± |11711.4041|
| | |none | 0|acc | 0.0000|± | 0.0000|
|boolq | 2|none | 0|acc | 0.3783|± | 0.0085|
|arc_easy | 1|none | 0|acc | 0.2593|± | 0.0090|
| | |none | 0|acc_norm | 0.2774|± | 0.0092|
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- seed: 80085
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 6.0703 | 0.0656 | 400 | 6.2332 | 0.1701 | 52428800 |
| 5.723 | 0.1313 | 800 | 5.9116 | 0.1893 | 104857600 |
| 5.5106 | 0.1969 | 1200 | 5.7516 | 0.1976 | 157286400 |
| 5.455 | 0.2626 | 1600 | 5.6427 | 0.2032 | 209715200 |
| 5.3236 | 0.3282 | 2000 | 5.5567 | 0.2103 | 262144000 |
| 5.2764 | 0.3938 | 2400 | 5.4919 | 0.2151 | 314572800 |
| 5.1625 | 0.4595 | 2800 | 5.4436 | 0.2176 | 367001600 |
| 5.1851 | 0.5251 | 3200 | 5.3975 | 0.2206 | 419430400 |
| 5.0618 | 0.5908 | 3600 | 5.3624 | 0.2199 | 471859200 |
| 5.0278 | 0.6564 | 4000 | 5.3242 | 0.2236 | 524288000 |
| 5.0389 | 0.7220 | 4400 | 5.2920 | 0.2264 | 576716800 |
| 4.9732 | 0.7877 | 4800 | 5.2674 | 0.2276 | 629145600 |
| 4.9375 | 0.8533 | 5200 | 5.2418 | 0.2292 | 681574400 |
| 4.9322 | 0.9190 | 5600 | 5.2166 | 0.2312 | 734003200 |
| 4.8818 | 0.9846 | 6000 | 5.1981 | 0.2315 | 786432000 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |