---
library_name: transformers
license: other
base_model: google/gemma-2-2b
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: polyalign
  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. -->

# polyalign

This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on the polyalign_train dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3660

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7654        | 0.1095 | 1000 | 1.2028          |
| 1.6802        | 0.2190 | 2000 | 1.2025          |
| 1.5967        | 0.3285 | 3000 | 1.2402          |
| 1.5228        | 0.4380 | 4000 | 1.2522          |
| 1.4704        | 0.5475 | 5000 | 1.2775          |
| 1.3997        | 0.6570 | 6000 | 1.2849          |
| 1.3373        | 0.7666 | 7000 | 1.3272          |
| 1.3105        | 0.8761 | 8000 | 1.3563          |
| 1.2906        | 0.9856 | 9000 | 1.3660          |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.9.1+rocm6.3
- Datasets 4.0.0
- Tokenizers 0.22.2