Mistral_AAID_mixed_train
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the AAID_mixed dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3641 | 0.2023 | 200 | 0.3063 |
0.2727 | 0.4047 | 400 | 0.2442 |
0.2004 | 0.6070 | 600 | 0.1586 |
0.1247 | 0.8093 | 800 | 0.0947 |
0.0706 | 1.0116 | 1000 | 0.0530 |
0.0385 | 1.2140 | 1200 | 0.0325 |
0.0227 | 1.4163 | 1400 | 0.0161 |
0.0129 | 1.6186 | 1600 | 0.0074 |
0.0058 | 1.8209 | 1800 | 0.0035 |
0.0024 | 2.0233 | 2000 | 0.0011 |
0.0007 | 2.2256 | 2200 | 0.0006 |
0.0004 | 2.4279 | 2400 | 0.0002 |
0.0002 | 2.6302 | 2600 | 0.0001 |
0.0001 | 2.8326 | 2800 | 0.0001 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Holmeister/Mistral_AAID_mixed_train_old
Base model
mistralai/Mistral-7B-v0.1