shawgpt-ft
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8143
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 |
---|---|---|---|
4.0111 | 0.9231 | 3 | 3.4383 |
3.7197 | 1.8462 | 6 | 3.1542 |
3.3433 | 2.7692 | 9 | 2.8819 |
2.2325 | 4.0 | 13 | 2.5118 |
2.6351 | 4.9231 | 16 | 2.2513 |
2.298 | 5.8462 | 19 | 2.0509 |
2.0805 | 6.7692 | 22 | 1.9310 |
1.4903 | 8.0 | 26 | 1.8460 |
1.9251 | 8.9231 | 29 | 1.8175 |
1.3554 | 9.2308 | 30 | 1.8143 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for harshi321/shawgpt-ft
Base model
mistralai/Mistral-7B-v0.1
Finetuned
mistralai/Mistral-7B-Instruct-v0.1
Quantized
TheBloke/Mistral-7B-Instruct-v0.1-GPTQ