metadata
tags:
- generated_from_trainer
datasets:
- /pfs/lustrep4/scratch/project_462000259/noah/instruct-datasets/askscience
metrics:
- accuracy
model-index:
- name: layer_13,14,15
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: >-
/pfs/lustrep4/scratch/project_462000259/noah/instruct-datasets/askscience
type: >-
/pfs/lustrep4/scratch/project_462000259/noah/instruct-datasets/askscience
metrics:
- name: Accuracy
type: accuracy
value: 0.27968436193888074
layer_13,14,15
This model is a fine-tuned version of /pfs/lustrep4/scratch/project_462000259/noah/instruct_1bil/transfer/pythia-deduped-1b-chat-base/ on the /pfs/lustrep4/scratch/project_462000259/noah/instruct-datasets/askscience dataset. It achieves the following results on the evaluation set:
- Loss: 5.4570
- Accuracy: 0.2797
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: 24
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 192
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 6000
Training results
Framework versions
- Transformers 4.27.0
- Pytorch 1.12.1+gitcb6c422
- Datasets 2.11.0
- Tokenizers 0.13.3