shawgpt-ft
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: 1.3426
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|
| 2.1898 | 0.5714 | 1 | 1.3977 |
| 1.0956 | 1.7143 | 3 | 1.3555 |
| 0.9584 | 2.8571 | 5 | 1.3268 |
| 0.9261 | 4.0 | 7 | 1.3375 |
| 1.9273 | 4.5714 | 8 | 1.3359 |
| 0.8619 | 5.7143 | 10 | 1.3284 |
| 0.8375 | 6.8571 | 12 | 1.3394 |
| 0.8695 | 8.0 | 14 | 1.3439 |
| 0.9186 | 8.5714 | 15 | 1.3426 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for 888Brogaard/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2 Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ