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