metadata
tags:
- generated_from_trainer
datasets:
- >-
/pfs/lustrep4/scratch/project_462000259/shared_datasets/modified_200/modified_200/
metrics:
- accuracy
model-index:
- name: >-
layer_0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: >-
/pfs/lustrep4/scratch/project_462000259/shared_datasets/modified_200/modified_200/
type: >-
/pfs/lustrep4/scratch/project_462000259/shared_datasets/modified_200/modified_200/
metrics:
- name: Accuracy
type: accuracy
value: 0.05919863214460186
layer_0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31
This model is a fine-tuned version of /pfs/lustrep4/scratch/project_462000259/shared_models/pythia-2.8b-deduped-base/pythia-2.8b-deduped on the /pfs/lustrep4/scratch/project_462000259/shared_datasets/modified_200/modified_200/ dataset. It achieves the following results on the evaluation set:
- Loss: 0.9966
- Accuracy: 0.0592
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 14484
Training results
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+rocm5.4.2
- Datasets 2.11.0
- Tokenizers 0.13.3