---
license: gemma
base_model: google/gemma-2-2b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-2b_hs2_accumulatesubsample_iter5_sftsd1
  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. -->

# collapse_gemma-2-2b_hs2_accumulatesubsample_iter5_sftsd1

This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1596
- Num Input Tokens Seen: 5092792

## 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: 8e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 1
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|
| No log        | 0      | 0    | 1.3909          | 0                 |
| 1.396         | 0.0535 | 5    | 1.2688          | 272480            |
| 1.1748        | 0.1070 | 10   | 1.1838          | 547328            |
| 1.12          | 0.1605 | 15   | 1.1718          | 821600            |
| 1.0808        | 0.2140 | 20   | 1.1633          | 1094936           |
| 0.8774        | 0.2676 | 25   | 1.1724          | 1374424           |
| 0.7922        | 0.3211 | 30   | 1.1880          | 1646160           |
| 0.8423        | 0.3746 | 35   | 1.1878          | 1922560           |
| 0.7508        | 0.4281 | 40   | 1.1777          | 2201456           |
| 0.6903        | 0.4816 | 45   | 1.1815          | 2480912           |
| 0.6497        | 0.5351 | 50   | 1.1695          | 2756496           |
| 0.6544        | 0.5886 | 55   | 1.1748          | 3029896           |
| 0.5257        | 0.6421 | 60   | 1.1744          | 3298912           |
| 0.607         | 0.6957 | 65   | 1.1630          | 3580736           |
| 0.5229        | 0.7492 | 70   | 1.1702          | 3850984           |
| 0.4844        | 0.8027 | 75   | 1.1632          | 4119888           |
| 0.5335        | 0.8562 | 80   | 1.1608          | 4389384           |
| 0.539         | 0.9097 | 85   | 1.1614          | 4662512           |
| 0.6048        | 0.9632 | 90   | 1.1580          | 4929312           |


### Framework versions

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