Downloads · 30 days
0
O0503HMA26
Litzy619/O0503HMA26
O0503HMA26 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 May 14, 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
- May 14, 2024
- Updated
- May 14, 2024
- SHA
- 7b686e2d
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. -->
O0503HMA26
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: 0.0555
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 |
|---|---|---|---|
| 2.294 | 0.09 | 10 | 0.1840 |
| 0.1641 | 0.18 | 20 | 0.1529 |
| 0.1475 | 0.27 | 30 | 0.1583 |
| 0.1555 | 0.36 | 40 | 0.1569 |
| 0.1515 | 0.45 | 50 | 0.1531 |
| 0.1518 | 0.54 | 60 | 0.1515 |
| 0.1548 | 0.63 | 70 | 0.1513 |
| 0.1512 | 0.73 | 80 | 0.1635 |
| 0.1502 | 0.82 | 90 | 0.1684 |
| 0.1537 | 0.91 | 100 | 0.1503 |
| 0.3316 | 1.0 | 110 | 1.8975 |
| 1.292 | 1.09 | 120 | 2.6843 |
| 0.8933 | 1.18 | 130 | 0.1791 |
| 0.2103 | 1.27 | 140 | 0.1633 |
| 0.21 | 1.36 | 150 | 0.1549 |
| 0.1529 | 1.45 | 160 | 0.1515 |
| 0.1515 | 1.54 | 170 | 0.1514 |
| 0.1605 | 1.63 | 180 | 0.1803 |
| 0.1572 | 1.72 | 190 | 0.1543 |
| 0.149 | 1.81 | 200 | 0.1566 |
| 0.1516 | 1.9 | 210 | 0.1474 |
| 0.1427 | 1.99 | 220 | 0.1292 |
| 0.113 | 2.08 | 230 | 0.0781 |
| 0.0768 | 2.18 | 240 | 0.0718 |
| 0.0696 | 2.27 | 250 | 0.0699 |
| 0.0745 | 2.36 | 260 | 0.0666 |
| 0.0694 | 2.45 | 270 | 0.0677 |
| 0.0595 | 2.54 | 280 | 0.0665 |
| 0.0634 | 2.63 | 290 | 0.0613 |
| 0.0672 | 2.72 | 300 | 0.0607 |
| 0.0576 | 2.81 | 310 | 0.0583 |
| 0.0582 | 2.9 | 320 | 0.0568 |
| 0.0614 | 2.99 | 330 | 0.0555 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- apache-2.0
- Created
- May 14, 2024
- Updated
- May 14, 2024