Downloads · 30 days
0
GOLM1
Litzy619/GOLM1
GOLM1 is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as gemma.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated May 2, 2024
Parameters
2.5B
20.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors10.1 GB · 99%
At a glance
- License
- gemma
- Access
- Public
- Created
- May 2, 2024
- Updated
- May 2, 2024
- SHA
- 12b7b1bd
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
GOLM1
This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1016
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 |
|---|---|---|---|
| 1.7996 | 0.09 | 10 | 1.4084 |
| 0.9949 | 0.18 | 20 | 0.5027 |
| 0.3011 | 0.27 | 30 | 0.1578 |
| 0.1527 | 0.36 | 40 | 0.1481 |
| 0.1447 | 0.45 | 50 | 0.1469 |
| 0.1451 | 0.54 | 60 | 0.1464 |
| 0.142 | 0.63 | 70 | 0.1422 |
| 0.1422 | 0.73 | 80 | 0.1372 |
| 0.1304 | 0.82 | 90 | 0.1289 |
| 0.1241 | 0.91 | 100 | 0.1269 |
| 0.1263 | 1.0 | 110 | 0.1302 |
| 0.1163 | 1.09 | 120 | 0.1185 |
| 0.1091 | 1.18 | 130 | 0.1211 |
| 0.1143 | 1.27 | 140 | 0.1143 |
| 0.1131 | 1.36 | 150 | 0.1113 |
| 0.1127 | 1.45 | 160 | 0.1115 |
| 0.1087 | 1.54 | 170 | 0.1073 |
| 0.1086 | 1.63 | 180 | 0.1064 |
| 0.1069 | 1.72 | 190 | 0.1053 |
| 0.1027 | 1.81 | 200 | 0.1047 |
| 0.1037 | 1.9 | 210 | 0.1022 |
| 0.1072 | 1.99 | 220 | 0.1029 |
| 0.0896 | 2.08 | 230 | 0.1056 |
| 0.0918 | 2.18 | 240 | 0.1024 |
| 0.0828 | 2.27 | 250 | 0.1026 |
| 0.0861 | 2.36 | 260 | 0.1022 |
| 0.0853 | 2.45 | 270 | 0.1049 |
| 0.0809 | 2.54 | 280 | 0.1028 |
| 0.0782 | 2.63 | 290 | 0.1021 |
| 0.0814 | 2.72 | 300 | 0.1021 |
| 0.0849 | 2.81 | 310 | 0.1019 |
| 0.0838 | 2.9 | 320 | 0.1016 |
| 0.0864 | 2.99 | 330 | 0.1016 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- gemma
- Created
- May 2, 2024
- Updated
- May 2, 2024