Downloads · 30 days
0
O0430HMA23
Litzy619/O0430HMA23
O0430HMA23 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Apr 30, 2024
Parameters
1.2B
5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors4.8 GB · 97%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024
- SHA
- 9d4115ff
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. -->
O0430HMA23
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0182
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 |
|---|---|---|---|
| 2.4506 | 0.09 | 10 | 0.1889 |
| 0.1655 | 0.18 | 20 | 0.1531 |
| 0.1485 | 0.27 | 30 | 0.1616 |
| 0.154 | 0.36 | 40 | 0.1569 |
| 0.1509 | 0.45 | 50 | 0.1534 |
| 0.1519 | 0.54 | 60 | 0.1516 |
| 0.1522 | 0.63 | 70 | 0.1477 |
| 0.151 | 0.73 | 80 | 0.1563 |
| 0.1471 | 0.82 | 90 | 0.1501 |
| 0.1488 | 0.91 | 100 | 0.1497 |
| 0.1506 | 1.0 | 110 | 0.1507 |
| 0.1467 | 1.09 | 120 | 0.1492 |
| 0.1468 | 1.18 | 130 | 0.1508 |
| 0.1471 | 1.27 | 140 | 0.1494 |
| 0.1487 | 1.36 | 150 | 0.1463 |
| 0.1348 | 1.45 | 160 | 0.1119 |
| 0.8389 | 1.54 | 170 | 0.0728 |
| 0.1309 | 1.63 | 180 | 0.0776 |
| 0.0795 | 1.72 | 190 | 0.0686 |
| 0.0655 | 1.81 | 200 | 0.0713 |
| 0.0538 | 1.9 | 210 | 0.0457 |
| 0.0396 | 1.99 | 220 | 0.0339 |
| 0.0517 | 2.08 | 230 | 0.0392 |
| 0.0346 | 2.18 | 240 | 0.0262 |
| 0.0254 | 2.27 | 250 | 0.0248 |
| 0.0294 | 2.36 | 260 | 0.0228 |
| 0.026 | 2.45 | 270 | 0.0211 |
| 0.0179 | 2.54 | 280 | 0.0206 |
| 0.0269 | 2.63 | 290 | 0.0193 |
| 0.0243 | 2.72 | 300 | 0.0204 |
| 0.0195 | 2.81 | 310 | 0.0183 |
| 0.0226 | 2.9 | 320 | 0.0183 |
| 0.0206 | 2.99 | 330 | 0.0182 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- apache-2.0
- Created
- Apr 30, 2024
- Updated
- Apr 30, 2024