gemma2b-coding-gpt4o-100k
This model is a fine-tuned version of google/gemma-2b on the llama-duo/synth_coding_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 1.6825
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6871 | 0.9979 | 235 | 1.4013 |
| 0.6707 | 2.0 | 471 | 1.3993 |
| 0.6047 | 2.9979 | 706 | 1.4091 |
| 0.5773 | 4.0 | 942 | 1.4428 |
| 0.5548 | 4.9979 | 1177 | 1.4904 |
| 0.5409 | 6.0 | 1413 | 1.5480 |
| 0.5151 | 6.9979 | 1648 | 1.6102 |
| 0.4987 | 8.0 | 1884 | 1.6578 |
| 0.4875 | 8.9979 | 2119 | 1.6813 |
| 0.4904 | 9.9788 | 2350 | 1.6825 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
google/gemma-2b