robotics_finetuned_text_perception
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: 0.1330
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|---|---|---|---|
| 1.1284 | 0.98 | 11 | 0.7789 |
| 0.6556 | 1.96 | 22 | 0.5358 |
| 0.4906 | 2.93 | 33 | 0.4536 |
| 0.3796 | 4.0 | 45 | 0.3670 |
| 0.3298 | 4.98 | 56 | 0.2929 |
| 0.2565 | 5.96 | 67 | 0.2295 |
| 0.2017 | 6.93 | 78 | 0.1827 |
| 0.1484 | 8.0 | 90 | 0.1500 |
| 0.138 | 8.98 | 101 | 0.1367 |
| 0.1226 | 9.78 | 110 | 0.1330 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for nourijel/robotics_finetuned_text_perception
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ