shawgpt-ft-rank15
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: 1.4708
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: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.6112 | 0.9231 | 3 | 4.0550 |
4.2025 | 1.8462 | 6 | 3.6361 |
3.7045 | 2.7692 | 9 | 3.2236 |
2.4446 | 4.0 | 13 | 2.7784 |
2.9141 | 4.9231 | 16 | 2.5251 |
2.5912 | 5.8462 | 19 | 2.2999 |
2.3012 | 6.7692 | 22 | 2.0951 |
1.557 | 8.0 | 26 | 1.8584 |
1.8593 | 8.9231 | 29 | 1.7346 |
1.7011 | 9.8462 | 32 | 1.6430 |
1.6199 | 10.7692 | 35 | 1.5651 |
1.1287 | 12.0 | 39 | 1.5022 |
1.4878 | 12.9231 | 42 | 1.4791 |
1.229 | 13.8462 | 45 | 1.4708 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for FrederikKlinkby/shawgpt-ft-rank15
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ