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---
license: gemma
base_model: jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: augmented_step_val_25_gemma-2-2b_hs2_iter1_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. -->
# augmented_step_val_25_gemma-2-2b_hs2_iter1_sftsd0
This model is a fine-tuned version of [jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2](https://huggingface.co/jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5241
- Num Input Tokens Seen: 7902160
## 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: 0
- 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 | 1.0950 | 0 |
| 1.4641 | 0.0363 | 5 | 1.0952 | 288056 |
| 1.2843 | 0.0726 | 10 | 1.1081 | 573696 |
| 1.179 | 0.1089 | 15 | 1.1363 | 864312 |
| 1.0141 | 0.1452 | 20 | 1.1791 | 1155592 |
| 0.9315 | 0.1815 | 25 | 1.2351 | 1442896 |
| 0.825 | 0.2178 | 30 | 1.3062 | 1738192 |
| 0.6513 | 0.2541 | 35 | 1.3937 | 2026640 |
| 0.5567 | 0.2904 | 40 | 1.4694 | 2311728 |
| 0.5304 | 0.3267 | 45 | 1.4723 | 2603472 |
| 0.372 | 0.3630 | 50 | 1.4773 | 2895216 |
| 0.3612 | 0.3993 | 55 | 1.4670 | 3177072 |
| 0.3167 | 0.4356 | 60 | 1.4953 | 3464608 |
| 0.2068 | 0.4719 | 65 | 1.5190 | 3749472 |
| 0.1664 | 0.5082 | 70 | 1.4786 | 4033064 |
| 0.2256 | 0.5445 | 75 | 1.4518 | 4326968 |
| 0.1704 | 0.5808 | 80 | 1.4577 | 4611416 |
| 0.1391 | 0.6171 | 85 | 1.5038 | 4903168 |
| 0.2488 | 0.6534 | 90 | 1.4373 | 5191528 |
| 0.1726 | 0.6897 | 95 | 1.5123 | 5474696 |
| 0.1696 | 0.7260 | 100 | 1.4582 | 5757304 |
| 0.1919 | 0.7623 | 105 | 1.4735 | 6047208 |
| 0.1987 | 0.7985 | 110 | 1.4654 | 6343824 |
| 0.256 | 0.8348 | 115 | 1.4215 | 6627376 |
| 0.0984 | 0.8711 | 120 | 1.5130 | 6915440 |
| 0.108 | 0.9074 | 125 | 1.4880 | 7206272 |
| 0.1414 | 0.9437 | 130 | 1.4197 | 7504304 |
| 0.1076 | 0.9800 | 135 | 1.5077 | 7784504 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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