mistral-codaspy
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0002
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: 2.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- 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: 5
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.7694 | 0.22 | 50 | 0.0199 |
0.0106 | 0.44 | 100 | 0.0061 |
0.0036 | 0.66 | 150 | 0.0018 |
0.0011 | 0.88 | 200 | 0.0006 |
0.0005 | 1.11 | 250 | 0.0004 |
0.0003 | 1.33 | 300 | 0.0003 |
0.0003 | 1.55 | 350 | 0.0002 |
0.0002 | 1.77 | 400 | 0.0002 |
0.0002 | 1.99 | 450 | 0.0002 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for dainis-boumber/mistral-codaspy
Base model
mistralai/Mistral-7B-v0.1