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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pile-instruct/ |
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metrics: |
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- accuracy |
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model-index: |
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- name: layer_4,5,6,7,8 |
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results: |
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- task: |
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type: text-generation |
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name: Causal Language Modeling |
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dataset: |
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name: pile-instruct/ |
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type: pile-instruct/ |
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split: None |
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metrics: |
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- type: accuracy |
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value: 0.38424293893426953 |
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name: Accuracy |
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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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# layer_4,5,6,7,8 |
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This model is a fine-tuned version of [P1ayer-1/pythia-deduped-1b-chat-base](https://huggingface.co/P1ayer-1/pythia-deduped-1b-chat-base) on the pile-instruct/ dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.9648 |
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- Accuracy: 0.3842 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 0.0001 |
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- train_batch_size: 12 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 96 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 6000 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 7.4574 | 0.1 | 200 | 0.1688 | 7.4961 | |
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| 7.0445 | 0.2 | 400 | 0.1997 | 7.0547 | |
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| 6.7483 | 0.3 | 600 | 0.2190 | 6.7930 | |
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| 6.4568 | 0.4 | 800 | 0.2376 | 6.5703 | |
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| 6.2865 | 0.5 | 1000 | 0.2552 | 6.375 | |
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| 6.1028 | 0.6 | 1200 | 0.2793 | 6.1484 | |
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| 5.8888 | 0.7 | 1400 | 0.2982 | 5.9570 | |
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| 5.7362 | 0.8 | 1600 | 0.3121 | 5.8008 | |
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| 5.6507 | 0.9 | 1800 | 0.3238 | 5.6797 | |
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| 5.565 | 1.0 | 2000 | 0.3318 | 5.5781 | |
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| 5.4688 | 1.1 | 2200 | 0.3392 | 5.4961 | |
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| 5.4044 | 1.2 | 2400 | 0.3456 | 5.4219 | |
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| 5.3323 | 1.3 | 2600 | 0.3516 | 5.3594 | |
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| 5.2598 | 1.4 | 2800 | 0.3562 | 5.3047 | |
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| 5.2159 | 1.5 | 3000 | 0.3596 | 5.2578 | |
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| 5.1992 | 1.6 | 3200 | 0.3638 | 5.2148 | |
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| 5.1429 | 1.69 | 3400 | 0.3672 | 5.1797 | |
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| 5.095 | 1.79 | 3600 | 0.3696 | 5.1445 | |
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| 5.0646 | 1.89 | 3800 | 0.3715 | 5.1172 | |
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| 5.059 | 1.99 | 4000 | 0.3742 | 5.0859 | |
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| 5.0152 | 2.09 | 4200 | 0.3756 | 5.0664 | |
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| 5.0251 | 2.19 | 4400 | 0.3769 | 5.0469 | |
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| 5.022 | 2.29 | 4600 | 0.3790 | 5.0273 | |
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| 4.9939 | 2.39 | 4800 | 0.3798 | 5.0156 | |
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| 4.924 | 2.49 | 5000 | 0.3811 | 5.0 | |
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| 4.9335 | 2.59 | 5200 | 0.3821 | 4.9883 | |
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| 4.9231 | 2.69 | 5400 | 0.3829 | 4.9805 | |
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| 4.8886 | 2.79 | 5600 | 0.3835 | 4.9727 | |
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| 4.9419 | 2.89 | 5800 | 0.3843 | 4.9648 | |
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| 4.9227 | 2.99 | 6000 | 0.3842 | 4.9648 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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## Wandb Report |
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https://wandb.ai/ontocord/pythia-1b-deduped-layer-test-min-pile-instruct/runs/zad9qli2 |
