File size: 3,791 Bytes
2c8738e f5e092e 2c8738e f5e092e 2c8738e f5e092e 2c8738e f5e092e 2c8738e 8c2acde 2c8738e 96dac12 2c8738e f5e092e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
---
license: apache-2.0
base_model: pszemraj/griffin-1024-llama3t-8layer-simplewiki-silu
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: griffin-1024-llama3t-8layer-simplewiki-silu-fineweb-1M_en-med-vN
results: []
datasets:
- BEE-spoke-data/fineweb-1M_en-med
language:
- en
---
# griffin-llama3t-8L-v0.02-fineweb
Pretraining experiment with griffin/recurrent_gemma arch. This one uses the Llama-3 tokenizer.
## Model description
Further training of [pszemraj/griffin-1024-llama3t-8layer-simplewiki-silu](https://huggingface.co/pszemraj/griffin-1024-llama3t-8layer-simplewiki-silu) on the BEE-spoke-data/fineweb-1M_en-med dataset.
It achieves the following results on the evaluation set:
- Loss: 5.6538
- Accuracy: 0.1881
- Num Input Tokens Seen: 766509056
## evals
tl;dr its bad/would need more training:
hf (pretrained=pszemraj/griffin-llama3t-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 | 0.4964|± | 0.0141|
|piqa | 1|none | 0|acc | 0.5332|± | 0.0116|
| | |none | 0|acc_norm | 0.5299|± | 0.0116|
|openbookqa | 1|none | 0|acc | 0.1280|± | 0.0150|
| | |none | 0|acc_norm | 0.2320|± | 0.0189|
|lambada_openai| 1|none | 0|perplexity|638060.0702|± |43608.0044|
| | |none | 0|acc | 0.0000|± | 0.0000|
|boolq | 2|none | 0|acc | 0.3783|± | 0.0085|
|arc_easy | 1|none | 0|acc | 0.2614|± | 0.0090|
| | |none | 0|acc_norm | 0.2744|± | 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 6.4019 | 0.0684 | 400 | 6.7690 | 0.1278 | 52428800 |
| 6.0547 | 0.1368 | 800 | 6.4214 | 0.1460 | 104857600 |
| 5.8133 | 0.2052 | 1200 | 6.2566 | 0.1550 | 157286400 |
| 5.7212 | 0.2736 | 1600 | 6.1411 | 0.1620 | 209715200 |
| 5.6175 | 0.3420 | 2000 | 6.0502 | 0.1669 | 262144000 |
| 5.5014 | 0.4104 | 2400 | 5.9827 | 0.1687 | 314572800 |
| 5.4882 | 0.4788 | 2800 | 5.9203 | 0.1731 | 367001600 |
| 5.3972 | 0.5472 | 3200 | 5.8614 | 0.1782 | 419430400 |
| 5.3983 | 0.6156 | 3600 | 5.8340 | 0.1773 | 471859200 |
| 5.3175 | 0.6840 | 4000 | 5.7916 | 0.1814 | 524288000 |
| 5.3014 | 0.7524 | 4400 | 5.7565 | 0.1814 | 576716800 |
| 5.2749 | 0.8208 | 4800 | 5.7303 | 0.1849 | 629145600 |
| 5.2264 | 0.8892 | 5200 | 5.6993 | 0.1850 | 681574400 |
| 5.2107 | 0.9576 | 5600 | 5.6745 | 0.1884 | 734003200 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |