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expert-min-pile-instruct

Text Generation
Transformers
PyTorch
gpt_neox
Generated from Trainer
text-generation-inference
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update model card README.md

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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: 0.20994595912408442
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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: 6.9437
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- - Accuracy: 0.2099
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  ## Model description
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@@ -49,27 +36,51 @@ More information needed
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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: 1
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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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- - gradient_accumulation_steps: 8
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- - total_train_batch_size: 64
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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: 1000
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 7.6017 | 0.02 | 200 | 7.5928 | 0.1605 |
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- | 7.1871 | 0.03 | 400 | 7.2690 | 0.1847 |
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- | 7.0356 | 0.05 | 600 | 7.0897 | 0.1980 |
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- | 6.93 | 0.07 | 800 | 6.9870 | 0.2064 |
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- | 6.9089 | 0.08 | 1000 | 6.9437 | 0.2099 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
@@ -78,7 +89,3 @@ The following hyperparameters were used during training:
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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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-
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-
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- ## Wandb Report
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- https://wandb.ai/ontocord/pythia-1b-deduped-layer-test-min-pile-instruct/runs/6hvfd11h
 
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  ---
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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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  model-index:
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+ - name: expert-min-pile-instruct
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
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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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+ # expert-min-pile-instruct
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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 None 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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  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 | 4.9727 | 0.3835 |
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+ | 4.9419 | 2.89 | 5800 | 4.9648 | 0.3843 |
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+ | 4.9227 | 2.99 | 6000 | 4.9648 | 0.3842 |
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  ### Framework versions
 
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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