mergeLlama-7b-Instruct-hf-quantized-peft
This model is a fine-tuned version of meta-llama/CodeLlama-7b-Instruct-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.2568
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: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 10.74 | 0.0122 | 20 | 7.4566 |
| 6.6528 | 0.0243 | 40 | 6.6315 |
| 6.4141 | 0.0365 | 60 | 6.4041 |
| 6.2451 | 0.0487 | 80 | 6.3026 |
| 6.1832 | 0.0608 | 100 | 6.2568 |
Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for curtisxu/mergeLlama-7b-Instruct-hf-quantized-peft
Base model
meta-llama/CodeLlama-7b-Instruct-hf