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---
license: gemma
base_model: google/gemma-2-27b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-27b_hs2_replace_iter4_sftsd0
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_iter4_sftsd0
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: 1.3266
- Num Input Tokens Seen: 4030192
## 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: 0
- 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 |
| 3.9014 | 0.0694 | 5 | 1.0629 | 278000 |
| 3.6407 | 0.1389 | 10 | 1.1530 | 559276 |
| 3.5129 | 0.2083 | 15 | 1.2057 | 839944 |
| 3.365 | 0.2778 | 20 | 1.2553 | 1123192 |
| 3.2314 | 0.3472 | 25 | 1.2937 | 1402000 |
| 3.0661 | 0.4167 | 30 | 1.3170 | 1675956 |
| 2.9861 | 0.4861 | 35 | 1.3117 | 1953884 |
| 2.9771 | 0.5556 | 40 | 1.3107 | 2238624 |
| 2.7982 | 0.625 | 45 | 1.3116 | 2521396 |
| 2.8816 | 0.6944 | 50 | 1.3106 | 2802856 |
| 2.8309 | 0.7639 | 55 | 1.3189 | 3077316 |
| 2.7512 | 0.8333 | 60 | 1.3098 | 3358448 |
| 2.7935 | 0.9028 | 65 | 1.3161 | 3643588 |
| 2.8647 | 0.9722 | 70 | 1.3220 | 3923824 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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