ZeroShot-3.3.9-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: 0.3844
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 |
---|---|---|---|
0.5036 | 0.06 | 100 | 0.4879 |
0.4561 | 0.12 | 200 | 0.4455 |
0.4255 | 0.19 | 300 | 0.4324 |
0.4111 | 0.25 | 400 | 0.4228 |
0.4102 | 0.31 | 500 | 0.4165 |
0.4059 | 0.37 | 600 | 0.4102 |
0.3959 | 0.43 | 700 | 0.4059 |
0.3904 | 0.5 | 800 | 0.4008 |
0.3902 | 0.56 | 900 | 0.3966 |
0.3895 | 0.62 | 1000 | 0.3930 |
0.3829 | 0.68 | 1100 | 0.3904 |
0.3885 | 0.74 | 1200 | 0.3879 |
0.3735 | 0.81 | 1300 | 0.3860 |
0.385 | 0.87 | 1400 | 0.3851 |
0.3773 | 0.93 | 1500 | 0.3846 |
0.3693 | 0.99 | 1600 | 0.3844 |
Framework versions
- PEFT 0.8.2
- 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-3.3.11-Mistral-7b-Multilanguage-3.2.0
Base model
mistralai/Mistral-7B-Instruct-v0.2