SequentialLearnerv2
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an Sequence Learner. It creates flow chart of logic to aid in solving problem set - Chain-Of-Thought, Abstraction, Hierarchial Metalearning 100K token finetuned on OpenPlatypus Math Dataset It achieves the following results on the evaluation set:
- Loss: 0.6176
Model description
More information needed
Intended uses & limitations
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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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.97 | 25 | 0.7079 |
| No log | 1.98 | 51 | 0.6083 |
| No log | 2.91 | 75 | 0.6176 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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mistralai/Mistral-7B-v0.1
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mistralai/Mistral-7B-Instruct-v0.1
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