ft-poc
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5077
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.6207 | 0.91 | 5 | 2.8472 |
2.1794 | 2.0 | 11 | 1.9461 |
1.8396 | 2.91 | 16 | 1.4070 |
1.0288 | 4.0 | 22 | 0.8795 |
0.7943 | 4.91 | 27 | 0.6335 |
0.5105 | 6.0 | 33 | 0.5606 |
0.5624 | 6.91 | 38 | 0.5307 |
0.4441 | 8.0 | 44 | 0.5145 |
0.5156 | 8.91 | 49 | 0.5080 |
0.2438 | 9.09 | 50 | 0.5077 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Farisya/ft-poc
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
Adapter
this model