---
license: gemma
base_model: google/gemma-2-27b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-27b_hs2_accumulate_iter2_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_accumulate_iter2_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: 0.9205
- Num Input Tokens Seen: 9260048

## 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                 |
| 1.6371        | 0.0278 | 5    | 1.0191          | 267540            |
| 1.6662        | 0.0555 | 10   | 0.9724          | 529072            |
| 1.3682        | 0.0833 | 15   | 0.9593          | 785900            |
| 1.465         | 0.1111 | 20   | 0.9571          | 1044336           |
| 1.4939        | 0.1388 | 25   | 0.9602          | 1302088           |
| 1.2547        | 0.1666 | 30   | 0.9604          | 1553344           |
| 1.3517        | 0.1944 | 35   | 0.9564          | 1808072           |
| 1.2594        | 0.2221 | 40   | 0.9531          | 2069656           |
| 1.122         | 0.2499 | 45   | 0.9501          | 2318876           |
| 1.1374        | 0.2777 | 50   | 0.9461          | 2574304           |
| 1.0402        | 0.3054 | 55   | 0.9441          | 2835460           |
| 0.9125        | 0.3332 | 60   | 0.9417          | 3100792           |
| 0.9725        | 0.3610 | 65   | 0.9371          | 3359628           |
| 1.0081        | 0.3888 | 70   | 0.9372          | 3624016           |
| 0.9675        | 0.4165 | 75   | 0.9346          | 3880016           |
| 1.0841        | 0.4443 | 80   | 0.9351          | 4126948           |
| 1.0015        | 0.4721 | 85   | 0.9313          | 4380144           |
| 1.0436        | 0.4998 | 90   | 0.9319          | 4645252           |
| 1.0193        | 0.5276 | 95   | 0.9298          | 4896128           |
| 1.0469        | 0.5554 | 100  | 0.9291          | 5148796           |
| 0.8706        | 0.5831 | 105  | 0.9269          | 5411164           |
| 0.8656        | 0.6109 | 110  | 0.9262          | 5663420           |
| 1.0066        | 0.6387 | 115  | 0.9243          | 5931756           |
| 0.8539        | 0.6664 | 120  | 0.9247          | 6192724           |
| 0.9333        | 0.6942 | 125  | 0.9233          | 6447744           |
| 0.8919        | 0.7220 | 130  | 0.9224          | 6704364           |
| 0.8694        | 0.7497 | 135  | 0.9221          | 6955692           |
| 0.916         | 0.7775 | 140  | 0.9211          | 7212120           |
| 0.9457        | 0.8053 | 145  | 0.9215          | 7469356           |
| 0.8997        | 0.8330 | 150  | 0.9199          | 7730508           |
| 0.8992        | 0.8608 | 155  | 0.9206          | 7979484           |
| 0.9604        | 0.8886 | 160  | 0.9191          | 8234480           |
| 0.9           | 0.9163 | 165  | 0.9186          | 8489188           |
| 0.9385        | 0.9441 | 170  | 0.9202          | 8745136           |
| 0.964         | 0.9719 | 175  | 0.9175          | 9000760           |
| 0.9423        | 0.9997 | 180  | 0.9205          | 9260048           |


### Framework versions

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