---
base_model: unsloth/gemma-2-9b
library_name: peft
license: gemma
tags:
- unsloth
- generated_from_trainer
model-index:
- name: gemma-2-9b_metamath_reverse
  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. -->

# gemma-2-9b_metamath_reverse

This model is a fine-tuned version of [unsloth/gemma-2-9b](https://huggingface.co./unsloth/gemma-2-9b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 10.7771

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7164        | 0.0211 | 13   | 0.9526          |
| 1.4875        | 0.0421 | 26   | 1.7775          |
| 1.8093        | 0.0632 | 39   | 2.4866          |
| 2.9457        | 0.0843 | 52   | 3.1388          |
| 4.2957        | 0.1053 | 65   | 4.3648          |
| 7.9729        | 0.1264 | 78   | 11.0147         |
| 10.8099       | 0.1474 | 91   | 9.4330          |
| 9.8556        | 0.1685 | 104  | 11.2095         |
| 11.4575       | 0.1896 | 117  | 11.8836         |
| 11.9399       | 0.2106 | 130  | 11.9231         |
| 11.9626       | 0.2317 | 143  | 11.9768         |
| 11.9547       | 0.2528 | 156  | 11.8762         |
| 11.9008       | 0.2738 | 169  | 11.9031         |
| 11.8209       | 0.2949 | 182  | 11.7070         |
| 11.7717       | 0.3159 | 195  | 11.8161         |
| 11.7063       | 0.3370 | 208  | 11.6304         |
| 11.5787       | 0.3581 | 221  | 11.7282         |
| 11.6212       | 0.3791 | 234  | 11.4066         |
| 11.4214       | 0.4002 | 247  | 11.2306         |
| 11.397        | 0.4213 | 260  | 11.3492         |
| 11.5241       | 0.4423 | 273  | 11.6393         |
| 11.5238       | 0.4634 | 286  | 11.2219         |
| 11.3261       | 0.4845 | 299  | 11.2667         |
| 11.3066       | 0.5055 | 312  | 11.2729         |
| 11.227        | 0.5266 | 325  | 11.0665         |
| 11.2074       | 0.5476 | 338  | 11.1924         |
| 11.0554       | 0.5687 | 351  | 11.0311         |
| 11.0567       | 0.5898 | 364  | 11.1885         |
| 11.1251       | 0.6108 | 377  | 10.8923         |
| 11.1682       | 0.6319 | 390  | 11.0041         |
| 10.9569       | 0.6530 | 403  | 11.0336         |
| 10.9747       | 0.6740 | 416  | 10.7973         |
| 10.9086       | 0.6951 | 429  | 10.8775         |
| 10.9555       | 0.7162 | 442  | 11.0885         |
| 10.8633       | 0.7372 | 455  | 10.9284         |
| 10.9128       | 0.7583 | 468  | 11.0310         |
| 10.9266       | 0.7793 | 481  | 11.0151         |
| 10.8317       | 0.8004 | 494  | 10.8168         |
| 10.7392       | 0.8215 | 507  | 10.8803         |
| 10.7123       | 0.8425 | 520  | 10.7858         |
| 10.8527       | 0.8636 | 533  | 10.8239         |
| 10.8007       | 0.8847 | 546  | 10.7503         |
| 10.7274       | 0.9057 | 559  | 10.7407         |
| 10.7662       | 0.9268 | 572  | 10.7765         |
| 10.7403       | 0.9478 | 585  | 10.7477         |
| 10.7315       | 0.9689 | 598  | 10.7644         |
| 10.7675       | 0.9900 | 611  | 10.7771         |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1