ZeroShot-3.3.14-Mistral-7b-Multilanguage-3.2.0
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: 0.3808
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: 2
- 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 |
---|---|---|---|
0.5047 | 0.06 | 100 | 0.4858 |
0.4654 | 0.12 | 200 | 0.4445 |
0.4173 | 0.19 | 300 | 0.4295 |
0.4042 | 0.25 | 400 | 0.4203 |
0.4084 | 0.31 | 500 | 0.4130 |
0.4002 | 0.37 | 600 | 0.4075 |
0.3916 | 0.43 | 700 | 0.4019 |
0.3915 | 0.5 | 800 | 0.3965 |
0.4022 | 0.56 | 900 | 0.3929 |
0.3842 | 0.62 | 1000 | 0.3895 |
0.3883 | 0.68 | 1100 | 0.3864 |
0.3815 | 0.74 | 1200 | 0.3841 |
0.3804 | 0.81 | 1300 | 0.3825 |
0.378 | 0.87 | 1400 | 0.3813 |
0.3681 | 0.93 | 1500 | 0.3809 |
0.3729 | 0.99 | 1600 | 0.3808 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for Weni/ZeroShot-3.3.14-Mistral-7b-Multilanguage-3.2.0
Base model
mistralai/Mistral-7B-Instruct-v0.2