gemma7b-coding-gpt4o-100k
This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_coding_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 3.9658
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|---|---|---|---|
| 0.5262 | 0.9989 | 470 | 1.3224 |
| 0.4826 | 2.0 | 941 | 1.3435 |
| 0.4369 | 2.9989 | 1411 | 1.4787 |
| 0.3819 | 4.0 | 1882 | 1.7432 |
| 0.3345 | 4.9989 | 2352 | 2.1234 |
| 0.2875 | 6.0 | 2823 | 2.5846 |
| 0.2319 | 6.9989 | 3293 | 3.1057 |
| 0.1968 | 8.0 | 3764 | 3.6609 |
| 0.1809 | 8.9989 | 4234 | 3.9400 |
| 0.1757 | 9.9894 | 4700 | 3.9658 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
google/gemma-7b