mistral-sum-r4a16
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: 1.7039
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 100
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.1541 | 0.0033 | 20 | 1.7466 |
1.7416 | 0.0067 | 40 | 1.7189 |
1.7384 | 0.0100 | 60 | 1.7093 |
1.7484 | 0.0134 | 80 | 1.7070 |
1.7301 | 0.0167 | 100 | 1.7039 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Taizer/mistral-sum-r4a16
Base model
mistralai/Mistral-7B-v0.1