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temp_gpt_neo
ICT3214-Group5/temp_gpt_neo
temp_gpt_neo is a text generation model from ICT3214-Group5. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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326
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Parameters
125M
7 GB on disk
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.safetensors501 MB · 99%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Model type
- gpt_neo
- Access
- Public
- Created
- Oct 27, 2024
- Updated
- Oct 28, 2024
- SHA
- 4ce8febd
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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. -->
temp_gpt_neo
This model is a fine-tuned version of EleutherAI/gpt-neo-125M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3814
- Bleu: 0.0
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| No log | 0.9091 | 5 | 7.9635 | 0.0 |
| No log | 2.0 | 11 | 5.3680 | 0.0 |
| No log | 2.9091 | 16 | 4.0323 | 0.0 |
| No log | 4.0 | 22 | 3.4255 | 0.0 |
| No log | 4.5455 | 25 | 3.3814 | 0.0 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
- Task
- Text Generation
- Library
- transformers
- Type
- gpt_neo
- License
- mit
- Created
- Oct 27, 2024
- Updated
- Oct 28, 2024