|
--- |
|
license: gemma |
|
base_model: google/gemma-2-2b |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: collapse_gemma-2-2b_hs2_accumulatesubsample_iter5_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-2-2b_hs2_accumulatesubsample_iter5_sftsd0 |
|
|
|
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: 1.1651 |
|
- Num Input Tokens Seen: 5121720 |
|
|
|
## 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 | 1.3909 | 0 | |
|
| 1.4516 | 0.0549 | 5 | 1.2704 | 281728 | |
|
| 1.2569 | 0.1098 | 10 | 1.1896 | 560496 | |
|
| 1.1565 | 0.1647 | 15 | 1.1711 | 843552 | |
|
| 1.0247 | 0.2196 | 20 | 1.1630 | 1124256 | |
|
| 0.999 | 0.2745 | 25 | 1.1730 | 1405360 | |
|
| 0.9404 | 0.3294 | 30 | 1.1667 | 1687800 | |
|
| 0.8346 | 0.3844 | 35 | 1.1909 | 1973600 | |
|
| 0.8733 | 0.4393 | 40 | 1.1780 | 2246208 | |
|
| 0.7992 | 0.4942 | 45 | 1.1868 | 2527096 | |
|
| 0.597 | 0.5491 | 50 | 1.1766 | 2813840 | |
|
| 0.6897 | 0.6040 | 55 | 1.1795 | 3093112 | |
|
| 0.6487 | 0.6589 | 60 | 1.1741 | 3372936 | |
|
| 0.6013 | 0.7138 | 65 | 1.1733 | 3651336 | |
|
| 0.6563 | 0.7687 | 70 | 1.1680 | 3931512 | |
|
| 0.5705 | 0.8236 | 75 | 1.1709 | 4216528 | |
|
| 0.6287 | 0.8785 | 80 | 1.1732 | 4498448 | |
|
| 0.5377 | 0.9334 | 85 | 1.1693 | 4778952 | |
|
| 0.6489 | 0.9883 | 90 | 1.1661 | 5063320 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
