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expert-min-pile-instruct
Multi-Domain-Expert-Learning/expert-min-pile-instruct
expert-min-pile-instruct is a text generation model from Multi-Domain-Expert-Learning. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- gpt_neox
- Access
- Public
- Created
- May 6, 2023
- Updated
- May 9, 2023
- SHA
- bde6b6a0
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Model card
From the Hugging Face model README
<!-- 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. -->
layer_4,5,6,7,8
This model is a fine-tuned version of P1ayer-1/pythia-deduped-1b-chat-base on the pile-instruct/ dataset. It achieves the following results on the evaluation set:
- Loss: 4.9648
- Accuracy: 0.3842
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 96
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 6000
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 7.4574 | 0.1 | 200 | 0.1688 | 7.4961 |
| 7.0445 | 0.2 | 400 | 0.1997 | 7.0547 |
| 6.7483 | 0.3 | 600 | 0.2190 | 6.7930 |
| 6.4568 | 0.4 | 800 | 0.2376 | 6.5703 |
| 6.2865 | 0.5 | 1000 | 0.2552 | 6.375 |
| 6.1028 | 0.6 | 1200 | 0.2793 | 6.1484 |
| 5.8888 | 0.7 | 1400 | 0.2982 | 5.9570 |
| 5.7362 | 0.8 | 1600 | 0.3121 | 5.8008 |
| 5.6507 | 0.9 | 1800 | 0.3238 | 5.6797 |
| 5.565 | 1.0 | 2000 | 0.3318 | 5.5781 |
| 5.4688 | 1.1 | 2200 | 0.3392 | 5.4961 |
| 5.4044 | 1.2 | 2400 | 0.3456 | 5.4219 |
| 5.3323 | 1.3 | 2600 | 0.3516 | 5.3594 |
| 5.2598 | 1.4 | 2800 | 0.3562 | 5.3047 |
| 5.2159 | 1.5 | 3000 | 0.3596 | 5.2578 |
| 5.1992 | 1.6 | 3200 | 0.3638 | 5.2148 |
| 5.1429 | 1.69 | 3400 | 0.3672 | 5.1797 |
| 5.095 | 1.79 | 3600 | 0.3696 | 5.1445 |
| 5.0646 | 1.89 | 3800 | 0.3715 | 5.1172 |
| 5.059 | 1.99 | 4000 | 0.3742 | 5.0859 |
| 5.0152 | 2.09 | 4200 | 0.3756 | 5.0664 |
| 5.0251 | 2.19 | 4400 | 0.3769 | 5.0469 |
| 5.022 | 2.29 | 4600 | 0.3790 | 5.0273 |
| 4.9939 | 2.39 | 4800 | 0.3798 | 5.0156 |
| 4.924 | 2.49 | 5000 | 0.3811 | 5.0 |
| 4.9335 | 2.59 | 5200 | 0.3821 | 4.9883 |
| 4.9231 | 2.69 | 5400 | 0.3829 | 4.9805 |
| 4.8886 | 2.79 | 5600 | 4.9727 | 0.3835 |
| 4.9419 | 2.89 | 5800 | 4.9648 | 0.3843 |
| 4.9227 | 2.99 | 6000 | 4.9648 | 0.3842 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
Wandb Report
https://wandb.ai/ontocord/pythia-1b-deduped-layer-test-min-pile-instruct/runs/kqlipkt3
- Task
- Text Generation
- Library
- transformers
- Type
- gpt_neox
- Created
- May 6, 2023
- Updated
- May 9, 2023