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V0410MP2_neo
Litzy619/V0410MP2_neo
V0410MP2_neo 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 mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Apr 11, 2024
Parameters
1.3B
12.5 GB on disk
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At a glance
- License
- mit
- Access
- Public
- Created
- Apr 11, 2024
- Updated
- Apr 11, 2024
- SHA
- ccfe4c27
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. -->
V0410MP2_neo
This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.8587
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: 20
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 14.6876 | 0.18 | 20 | 14.8238 |
| 15.6833 | 0.36 | 40 | 15.4468 |
| 12.87 | 0.54 | 60 | 10.7786 |
| 5.4953 | 0.73 | 80 | 4.9276 |
| 8.9421 | 0.91 | 100 | 8.9857 |
| 9.9807 | 1.09 | 120 | 9.7099 |
| 9.1809 | 1.27 | 140 | 9.2579 |
| 6.9349 | 1.45 | 160 | 5.9443 |
| 5.8015 | 1.63 | 180 | 5.9521 |
| 5.6365 | 1.81 | 200 | 5.7121 |
| 5.6957 | 1.99 | 220 | 5.8587 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 11, 2024
- Updated
- Apr 11, 2024