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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_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
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