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G0521HMA26H1
Litzy619/G0521HMA26H1
G0521HMA26H1 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. --
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Public
Updated May 21, 2024
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At a glance
- License
- gemma
- Access
- Public
- Created
- May 21, 2024
- Updated
- May 21, 2024
- SHA
- 5586d9ec
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. -->
G0521HMA26H1
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: 0.4153
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 |
|---|---|---|---|
| 1.7533 | 0.09 | 10 | 1.4934 |
| 1.0624 | 0.18 | 20 | 0.7710 |
| 0.393 | 0.27 | 30 | 0.2162 |
| 0.1584 | 0.36 | 40 | 0.2425 |
| 0.1475 | 0.45 | 50 | 0.3888 |
| 0.1494 | 0.54 | 60 | 0.3249 |
| 0.1472 | 0.63 | 70 | 0.4650 |
| 0.6741 | 0.73 | 80 | 0.2848 |
| 0.1413 | 0.82 | 90 | 0.3718 |
| 0.1393 | 0.91 | 100 | 0.2967 |
| 0.1353 | 1.0 | 110 | 0.4193 |
| 0.1291 | 1.09 | 120 | 0.5094 |
| 0.121 | 1.18 | 130 | 0.3007 |
| 0.1249 | 1.27 | 140 | 0.2038 |
| 0.1256 | 1.36 | 150 | 0.1808 |
| 0.1223 | 1.45 | 160 | 0.2009 |
| 0.1147 | 1.54 | 170 | 0.3312 |
| 0.1162 | 1.63 | 180 | 0.2481 |
| 0.1168 | 1.72 | 190 | 0.2108 |
| 0.1127 | 1.81 | 200 | 0.4134 |
| 0.112 | 1.9 | 210 | 0.2823 |
| 0.1098 | 1.99 | 220 | 0.3958 |
| 0.0993 | 2.08 | 230 | 0.4361 |
| 0.101 | 2.18 | 240 | 0.5045 |
| 0.0935 | 2.27 | 250 | 0.3612 |
| 0.0961 | 2.36 | 260 | 0.3679 |
| 0.0941 | 2.45 | 270 | 0.3548 |
| 0.0892 | 2.54 | 280 | 0.3754 |
| 0.0866 | 2.63 | 290 | 0.3601 |
| 0.0914 | 2.72 | 300 | 0.3955 |
| 0.0947 | 2.81 | 310 | 0.4108 |
| 0.0942 | 2.9 | 320 | 0.4147 |
| 0.0941 | 2.99 | 330 | 0.4153 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- gemma
- Created
- May 21, 2024
- Updated
- May 21, 2024