|
--- |
|
license: gemma |
|
base_model: google/gemma-2b |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: G0514BMA5b |
|
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. --> |
|
|
|
# G0514BMA5b |
|
|
|
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: -17.5764 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine_with_restarts |
|
- lr_scheduler_warmup_steps: 80 |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| -0.1378 | 0.09 | 10 | -0.4063 | |
|
| -0.7754 | 0.18 | 20 | -1.3256 | |
|
| -1.8887 | 0.27 | 30 | -2.7074 | |
|
| -3.4996 | 0.36 | 40 | -4.6101 | |
|
| -5.6334 | 0.45 | 50 | -7.0234 | |
|
| -8.1253 | 0.54 | 60 | -9.6448 | |
|
| -10.8034 | 0.63 | 70 | -12.2239 | |
|
| -13.2442 | 0.73 | 80 | -14.4267 | |
|
| -15.137 | 0.82 | 90 | -15.8906 | |
|
| -16.2451 | 0.91 | 100 | -16.5978 | |
|
| -16.7446 | 1.0 | 110 | -16.9186 | |
|
| -17.0061 | 1.09 | 120 | -17.0987 | |
|
| -17.1516 | 1.18 | 130 | -17.2214 | |
|
| -17.2598 | 1.27 | 140 | -17.3048 | |
|
| -17.3215 | 1.36 | 150 | -17.3631 | |
|
| -17.3805 | 1.45 | 160 | -17.4073 | |
|
| -17.4204 | 1.54 | 170 | -17.4427 | |
|
| -17.455 | 1.63 | 180 | -17.4700 | |
|
| -17.4781 | 1.72 | 190 | -17.4923 | |
|
| -17.501 | 1.81 | 200 | -17.5113 | |
|
| -17.5135 | 1.9 | 210 | -17.5260 | |
|
| -17.5294 | 1.99 | 220 | -17.5379 | |
|
| -17.5391 | 2.08 | 230 | -17.5475 | |
|
| -17.5526 | 2.18 | 240 | -17.5551 | |
|
| -17.5589 | 2.27 | 250 | -17.5616 | |
|
| -17.5631 | 2.36 | 260 | -17.5665 | |
|
| -17.5685 | 2.45 | 270 | -17.5701 | |
|
| -17.5727 | 2.54 | 280 | -17.5724 | |
|
| -17.5698 | 2.63 | 290 | -17.5743 | |
|
| -17.5709 | 2.72 | 300 | -17.5755 | |
|
| -17.5732 | 2.81 | 310 | -17.5761 | |
|
| -17.5761 | 2.9 | 320 | -17.5764 | |
|
| -17.5794 | 2.99 | 330 | -17.5764 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.0 |
|
|
