---
library_name: transformers
license: other
base_model: nvidia/Minitron-8B-Base
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: minitron-8b-tulu-v2-mix
  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. -->

# minitron-8b-tulu-v2-mix

This model is a fine-tuned version of [nvidia/Minitron-8B-Base](https://huggingface.co/nvidia/Minitron-8B-Base) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6678

## 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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- 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: 0.03
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8625        | 0.9992 | 566  | 0.7793          |
| 0.724         | 1.9992 | 1132 | 0.6678          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1