|
--- |
|
license: gemma |
|
base_model: google/gemma-2b |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: G0514HMA15H |
|
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. --> |
|
|
|
# G0514HMA15H |
|
|
|
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: -17.8971 |
|
|
|
## 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: 100 |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.9162 | 0.09 | 10 | 0.0830 | |
|
| -0.7664 | 0.18 | 20 | -2.0466 | |
|
| -3.27 | 0.27 | 30 | -4.9484 | |
|
| -6.242 | 0.36 | 40 | -7.9963 | |
|
| -9.1799 | 0.45 | 50 | -10.7742 | |
|
| -11.7646 | 0.54 | 60 | -13.2319 | |
|
| -14.1063 | 0.63 | 70 | -15.1473 | |
|
| -15.7143 | 0.73 | 80 | -16.3945 | |
|
| -16.7127 | 0.82 | 90 | -17.0741 | |
|
| -17.2299 | 0.91 | 100 | -17.4041 | |
|
| -17.4683 | 1.0 | 110 | -17.5479 | |
|
| -17.5857 | 1.09 | 120 | -17.6235 | |
|
| -17.6418 | 1.18 | 130 | -17.6631 | |
|
| -17.6771 | 1.27 | 140 | -17.6957 | |
|
| -17.703 | 1.36 | 150 | -17.7160 | |
|
| -17.7218 | 1.45 | 160 | -17.7272 | |
|
| -17.7369 | 1.54 | 170 | -17.7463 | |
|
| -17.7561 | 1.63 | 180 | -17.7646 | |
|
| -17.7704 | 1.72 | 190 | -17.7808 | |
|
| -17.7897 | 1.81 | 200 | -17.7972 | |
|
| -17.8056 | 1.9 | 210 | -17.8223 | |
|
| -17.8326 | 1.99 | 220 | -17.8447 | |
|
| -17.8508 | 2.08 | 230 | -17.8658 | |
|
| -17.8699 | 2.18 | 240 | -17.8773 | |
|
| -17.8777 | 2.27 | 250 | -17.8862 | |
|
| -17.8827 | 2.36 | 260 | -17.8912 | |
|
| -17.889 | 2.45 | 270 | -17.8936 | |
|
| -17.8917 | 2.54 | 280 | -17.8948 | |
|
| -17.8936 | 2.63 | 290 | -17.8942 | |
|
| -17.8949 | 2.72 | 300 | -17.8967 | |
|
| -17.8934 | 2.81 | 310 | -17.8970 | |
|
| -17.8964 | 2.9 | 320 | -17.8971 | |
|
| -17.8956 | 2.99 | 330 | -17.8971 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.0 |
|
|
