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---
license: gemma
base_model: google/gemma-2-2b
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: collapse_gemma-2-2b_hs2_accumulatesubsample_iter18_sftsd2
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-2-2b_hs2_accumulatesubsample_iter18_sftsd2
This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2146
- Num Input Tokens Seen: 4982224
## 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: 2
- 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 | 1.3909 | 0 |
| 1.2659 | 0.0529 | 5 | 1.2807 | 264312 |
| 1.0915 | 0.1059 | 10 | 1.2298 | 531088 |
| 0.9617 | 0.1588 | 15 | 1.2146 | 797680 |
| 0.8165 | 0.2118 | 20 | 1.2558 | 1063768 |
| 0.6736 | 0.2647 | 25 | 1.2705 | 1333352 |
| 0.6868 | 0.3177 | 30 | 1.2647 | 1594824 |
| 0.5659 | 0.3706 | 35 | 1.2549 | 1858024 |
| 0.4964 | 0.4236 | 40 | 1.2572 | 2122648 |
| 0.4903 | 0.4765 | 45 | 1.2329 | 2390872 |
| 0.4303 | 0.5295 | 50 | 1.2455 | 2656160 |
| 0.5471 | 0.5824 | 55 | 1.2231 | 2921864 |
| 0.4603 | 0.6353 | 60 | 1.2356 | 3187064 |
| 0.4218 | 0.6883 | 65 | 1.2259 | 3449192 |
| 0.4204 | 0.7412 | 70 | 1.2386 | 3712440 |
| 0.4478 | 0.7942 | 75 | 1.2208 | 3978048 |
| 0.4628 | 0.8471 | 80 | 1.2195 | 4239360 |
| 0.3803 | 0.9001 | 85 | 1.2154 | 4498248 |
| 0.452 | 0.9530 | 90 | 1.2053 | 4767016 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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