metadata

library_name: transformers
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - HuggingFaceTB/Magpie-Pro-300K-Filtered-H4
  - HuggingFaceTB/self-oss-instruct-sc2-H4
  - HuggingFaceTB/OpenHermes-2.5-H4
  - HuggingFaceTB/everyday-conversations-llama3.1-2k
  - HuggingFaceTB/instruct-data-basics-smollm-H4
model-index:
  - name: monet-vd-1.4B-100BT-chat-hf
    results: []

monet-vd-1.4B-100BT-chat-hf

This model is a fine-tuned version of monet-vd-1.4B-100BT-hf on the HuggingFaceTB/Magpie-Pro-300K-Filtered-H4, the HuggingFaceTB/self-oss-instruct-sc2-H4, the HuggingFaceTB/OpenHermes-2.5-H4, the HuggingFaceTB/everyday-conversations-llama3.1-2k and the HuggingFaceTB/instruct-data-basics-smollm-H4 datasets. It achieves the following results on the evaluation set:

Loss: 1.1664

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: 0.0003
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
total_train_batch_size: 128
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.8032	0.9988	502	1.1664

Framework versions

Transformers 4.44.2
Pytorch 2.4.1
Datasets 2.21.0
Tokenizers 0.19.1