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---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Summary4500_M2_1000steps_1e7rate_SFT
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. -->
# Summary4500_M2_1000steps_1e7rate_SFT
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0586
## 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: 1e-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.0168 | 0.0112 | 50 | 1.9854 |
| 1.3848 | 0.0224 | 100 | 1.3059 |
| 0.1374 | 0.0336 | 150 | 0.1142 |
| 0.0099 | 0.0448 | 200 | 0.0587 |
| 0.0076 | 0.0559 | 250 | 0.0581 |
| 0.0073 | 0.0671 | 300 | 0.0580 |
| 0.0071 | 0.0783 | 350 | 0.0587 |
| 0.0071 | 0.0895 | 400 | 0.0586 |
| 0.0069 | 0.1007 | 450 | 0.0589 |
| 0.0068 | 0.1119 | 500 | 0.0586 |
| 0.0068 | 0.1231 | 550 | 0.0586 |
| 0.0067 | 0.1343 | 600 | 0.0588 |
| 0.0067 | 0.1454 | 650 | 0.0589 |
| 0.0066 | 0.1566 | 700 | 0.0590 |
| 0.0066 | 0.1678 | 750 | 0.0587 |
| 0.0066 | 0.1790 | 800 | 0.0588 |
| 0.0066 | 0.1902 | 850 | 0.0588 |
| 0.0066 | 0.2014 | 900 | 0.0586 |
| 0.0066 | 0.2126 | 950 | 0.0586 |
| 0.0066 | 0.2238 | 1000 | 0.0586 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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