shawgpt-ft-model4
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: 2.8009
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: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.6424 | 0.9231 | 3 | 4.2062 |
4.5277 | 1.8462 | 6 | 4.0429 |
4.2535 | 2.7692 | 9 | 3.7825 |
2.9545 | 4.0 | 13 | 3.4616 |
3.6837 | 4.9231 | 16 | 3.2524 |
3.4407 | 5.8462 | 19 | 3.0824 |
3.2698 | 6.7692 | 22 | 2.9541 |
2.3491 | 8.0 | 26 | 2.8439 |
3.0525 | 8.9231 | 29 | 2.8052 |
2.0563 | 9.2308 | 30 | 2.8009 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for timewanderer/shawgpt-ft-model4
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ