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# MetaMath-Cybertron-Starling-Ruby

This model is a fine-tuned version of [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0319

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0913        | 0.39  | 50   | 1.0976          |
| 1.0399        | 0.78  | 100  | 1.0319          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "base_model": "Q-bert/MetaMath-Cybertron-Starling", "model-index": [{"name": "MetaMath-Cybertron-Starling-Ruby", "results": []}]}
transformers safetensors mistral text-generation generated_from_trainer conversational base_model:Q-bert/MetaMath-Cybertron-Starling license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us