ZeroShot-3.3.34-Mistral-7b-Multilanguage-3.3.0
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3779
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: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.4843 | 0.09 | 100 | 0.4538 |
0.4334 | 0.17 | 200 | 0.4199 |
0.3905 | 0.26 | 300 | 0.4081 |
0.4113 | 0.34 | 400 | 0.4017 |
0.4019 | 0.43 | 500 | 0.3948 |
0.38 | 0.51 | 600 | 0.3901 |
0.3883 | 0.6 | 700 | 0.3860 |
0.3894 | 0.68 | 800 | 0.3826 |
0.3679 | 0.77 | 900 | 0.3800 |
0.3764 | 0.85 | 1000 | 0.3784 |
0.3717 | 0.94 | 1100 | 0.3779 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Weni/ZeroShot-3.3.34-Mistral-7b-Multilanguage-3.3.0
Base model
mistralai/Mistral-7B-Instruct-v0.2