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---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: storage/context
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# storage/context
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0253
## 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: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1557 | 0.01 | 1 | 0.1552 |
| 0.0936 | 0.05 | 6 | 0.0695 |
| 0.0447 | 0.1 | 12 | 0.0413 |
| 0.0347 | 0.16 | 18 | 0.0357 |
| 0.0314 | 0.21 | 24 | 0.0324 |
| 0.0306 | 0.26 | 30 | 0.0309 |
| 0.0276 | 0.31 | 36 | 0.0294 |
| 0.028 | 0.36 | 42 | 0.0284 |
| 0.0307 | 0.41 | 48 | 0.0281 |
| 0.0276 | 0.47 | 54 | 0.0274 |
| 0.0251 | 0.52 | 60 | 0.0267 |
| 0.0244 | 0.57 | 66 | 0.0269 |
| 0.0268 | 0.62 | 72 | 0.0263 |
| 0.0249 | 0.67 | 78 | 0.0262 |
| 0.0252 | 0.73 | 84 | 0.0258 |
| 0.0259 | 0.78 | 90 | 0.0257 |
| 0.0241 | 0.83 | 96 | 0.0255 |
| 0.0241 | 0.88 | 102 | 0.0254 |
| 0.0253 | 0.93 | 108 | 0.0254 |
| 0.0234 | 0.98 | 114 | 0.0253 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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