---
license: gemma
base_model: google/gemma-2-27b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-27b_hs2_replace_iter1_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-2-27b_hs2_replace_iter1_sftsd1

This model is a fine-tuned version of [google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9050
- Num Input Tokens Seen: 5254884

## 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: 4
- eval_batch_size: 16
- seed: 1
- gradient_accumulation_steps: 32
- 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    | 1.1282          | 0                 |
| 0.9865        | 0.0511 | 5    | 0.9815          | 260128            |
| 0.9827        | 0.1021 | 10   | 0.9503          | 527396            |
| 0.9415        | 0.1532 | 15   | 0.9387          | 803280            |
| 0.9777        | 0.2043 | 20   | 0.9341          | 1074404           |
| 0.896         | 0.2553 | 25   | 0.9291          | 1348060           |
| 0.9836        | 0.3064 | 30   | 0.9259          | 1614960           |
| 0.8868        | 0.3575 | 35   | 0.9217          | 1884844           |
| 0.9037        | 0.4086 | 40   | 0.9192          | 2154208           |
| 0.9543        | 0.4596 | 45   | 0.9170          | 2424544           |
| 0.8617        | 0.5107 | 50   | 0.9155          | 2690292           |
| 0.9376        | 0.5618 | 55   | 0.9136          | 2962944           |
| 0.9256        | 0.6128 | 60   | 0.9114          | 3234692           |
| 0.8981        | 0.6639 | 65   | 0.9102          | 3510980           |
| 0.904         | 0.7150 | 70   | 0.9086          | 3790388           |
| 0.8904        | 0.7660 | 75   | 0.9081          | 4069200           |
| 0.9635        | 0.8171 | 80   | 0.9078          | 4338748           |
| 0.9016        | 0.8682 | 85   | 0.9061          | 4606552           |
| 0.8514        | 0.9192 | 90   | 0.9062          | 4877900           |
| 0.8992        | 0.9703 | 95   | 0.9058          | 5147172           |


### Framework versions

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