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RafaelZequeira_-_starcoderbase-1b-cucumber-copilot-gguf
RichardErkhov/RafaelZequeira_-_starcoderbase-1b-cucumber-copilot-gguf
RafaelZequeira_-_starcoderbase-1b-cucumber-copilot-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Oct 3, 2024
- Updated
- Oct 3, 2024
- SHA
- d0a958ed
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
starcoderbase-1b-cucumber-copilot - GGUF
- Model creator: https://huggingface.co/RafaelZequeira/
- Original model: https://huggingface.co/RafaelZequeira/starcoderbase-1b-cucumber-copilot/
Original model description:
license: bigcode-openrail-m tags:
- generated_from_trainer base_model: bigcode/starcoderbase-1b model-index:
- name: starcoderbase-1b-cucumber-copilot results: []
<!-- 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. -->
starcoderbase-1b-cucumber-copilot
This model is a fine-tuned version of bigcode/starcoderbase-1b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6377
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6697 | 0.25 | 250 | 0.6523 |
| 0.4537 | 0.5 | 500 | 0.6328 |
| 0.3829 | 0.75 | 750 | 0.6309 |
| 0.3245 | 1.0 | 1000 | 0.6377 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Created
- Oct 3, 2024
- Updated
- Oct 3, 2024