---
library_name: transformers
license: other
base_model: ontocord/1.7b-MixtureVitae-300BT-v1-long_instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: opensci_full_sft_fsdp_offload
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# opensci_full_sft_fsdp_offload

This model is a fine-tuned version of [ontocord/1.7b-MixtureVitae-300BT-v1](https://huggingface.co/ontocord/1.7b-MixtureVitae-300BT-v1) on the smoltalk, the longalign and the sealong datasets.
The model extends the context length of base model from 4096 to 16384 tokens.

### NOTE: Because the post-training data is no longer strictly public domain, cc-by and .gov, please do not depend on these constraints on the model output. This is an experimental model.

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 512
- 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: 0.05
- num_epochs: 1.0

### Training results



### Framework versions

- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4