metadata

library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
  - trl
  - sft
  - generated_from_trainer
datasets:
  - JunxiongWang/sftdataset
model-index:
  - name: 1b_distill_width_prune
    results: []

1b_distill_width_prune

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on the JunxiongWang/sftdataset dataset. It achieves the following results on the evaluation set:

Loss: 1.5712

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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 16
total_train_batch_size: 64
total_eval_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.01
training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss
1.3657	0.0413	10000	1.7362
1.2947	0.0827	20000	1.5713

Framework versions

Transformers 4.47.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.20.0
Tokenizers 0.20.3