finetune_deepspeed_deepseek
This model is a fine-tuned version of deepseek-ai/deepseek-coder-6.7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2286
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: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- 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: 0.03
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1482 | 1.0 | 1559 | 0.2420 |
| 0.0969 | 2.0 | 3118 | 0.2178 |
| 0.0761 | 3.0 | 4677 | 0.1981 |
| 0.0561 | 4.0 | 6236 | 0.1966 |
| 0.0469 | 5.0 | 7795 | 0.1977 |
| 0.0401 | 6.0 | 9354 | 0.1979 |
| 0.032 | 7.0 | 10913 | 0.2009 |
| 0.028 | 8.0 | 12472 | 0.2091 |
| 0.0254 | 9.0 | 14031 | 0.2252 |
| 0.0275 | 10.0 | 15590 | 0.2286 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Berkem/finetune_deepspeed_deepseek
Base model
deepseek-ai/deepseek-coder-6.7b-instruct