ZeroShot-3.3.28-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: 0.0501
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 |
---|---|---|---|
0.111 | 0.06 | 100 | 0.1583 |
0.1678 | 0.12 | 200 | 0.1279 |
0.1345 | 0.19 | 300 | 0.1216 |
0.1432 | 0.25 | 400 | 0.1087 |
0.1136 | 0.31 | 500 | 0.1330 |
0.1208 | 0.37 | 600 | 0.1074 |
0.0972 | 0.43 | 700 | 0.1033 |
0.115 | 0.5 | 800 | 0.0860 |
0.0946 | 0.56 | 900 | 0.0953 |
0.0702 | 0.62 | 1000 | 0.0731 |
0.0671 | 0.68 | 1100 | 0.0645 |
0.0679 | 0.74 | 1200 | 0.0604 |
0.0632 | 0.81 | 1300 | 0.0558 |
0.0492 | 0.87 | 1400 | 0.0529 |
0.048 | 0.93 | 1500 | 0.0510 |
0.0488 | 0.99 | 1600 | 0.0501 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Weni/ZeroShot-3.3.28-Mistral-7b-Multilanguage-3.2.0
Base model
mistralai/Mistral-7B-Instruct-v0.2