Downloads · 30 days
0
V0305P3
Litzy619/V0305P3
V0305P3 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 other.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Mar 12, 2024
Parameters
6.8B
42.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors13.8 GB · 98%
Parameter types
How the weights are stored.
F166.7B · 99%
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. -->
V0305P3
This model is a fine-tuned version of yahma/llama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0716
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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: 20
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5189 | 0.09 | 10 | 0.1892 |
| 0.1724 | 0.17 | 20 | 0.1543 |
| 0.1556 | 0.26 | 30 | 0.1534 |
| 0.1522 | 0.34 | 40 | 0.1523 |
| 0.1512 | 0.43 | 50 | 0.1487 |
| 0.1563 | 0.51 | 60 | 0.1495 |
| 0.1515 | 0.6 | 70 | 0.1474 |
| 0.1514 | 0.68 | 80 | 0.1419 |
| 0.1389 | 0.77 | 90 | 0.1194 |
| 0.1287 | 0.85 | 100 | 0.1003 |
| 0.1242 | 0.94 | 110 | 0.0968 |
| 0.1122 | 1.02 | 120 | 0.1009 |
| 0.1066 | 1.11 | 130 | 0.1001 |
| 0.0971 | 1.19 | 140 | 0.0963 |
| 0.0957 | 1.28 | 150 | 0.0882 |
| 0.0928 | 1.37 | 160 | 0.0883 |
| 0.0917 | 1.45 | 170 | 0.0809 |
| 0.0832 | 1.54 | 180 | 0.0893 |
| 0.085 | 1.62 | 190 | 0.0865 |
| 0.0906 | 1.71 | 200 | 0.0773 |
| 0.0879 | 1.79 | 210 | 0.0748 |
| 0.0852 | 1.88 | 220 | 0.0674 |
| 0.0796 | 1.96 | 230 | 0.0717 |
| 0.0674 | 2.05 | 240 | 0.0711 |
| 0.0518 | 2.13 | 250 | 0.0751 |
| 0.0521 | 2.22 | 260 | 0.0739 |
| 0.0504 | 2.3 | 270 | 0.0770 |
| 0.0556 | 2.39 | 280 | 0.0730 |
| 0.0605 | 2.47 | 290 | 0.0725 |
| 0.0515 | 2.56 | 300 | 0.0759 |
| 0.0526 | 2.65 | 310 | 0.0711 |
| 0.0494 | 2.73 | 320 | 0.0716 |
| 0.0518 | 2.82 | 330 | 0.0724 |
| 0.0508 | 2.9 | 340 | 0.0716 |
| 0.0509 | 2.99 | 350 | 0.0716 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- other
- Created
- Mar 5, 2024
- Updated
- Mar 12, 2024