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---
library_name: transformers
license: other
base_model: nvidia/Minitron-4B-Base
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- allenai/tulu-v2-sft-mixture
model-index:
- name: minitron-4b-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-4b-tulu-v2-mix
This model is a fine-tuned version of [nvidia/Minitron-4B-Base](https://huggingface.co/nvidia/Minitron-4B-Base) on the allenai/tulu-v2-sft-mixture dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1978
## 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: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.0088 | 5 | 1.1978 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1
|