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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: UTI_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. -->
# UTI_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: 1.1047
## 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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.4021 | 0.3333 | 25 | 2.3941 |
| 2.3235 | 0.6667 | 50 | 2.2471 |
| 2.0863 | 1.0 | 75 | 1.9386 |
| 1.6662 | 1.3333 | 100 | 1.5791 |
| 1.2956 | 1.6667 | 125 | 1.2544 |
| 1.214 | 2.0 | 150 | 1.2116 |
| 1.202 | 2.3333 | 175 | 1.1861 |
| 1.1813 | 2.6667 | 200 | 1.1668 |
| 1.1696 | 3.0 | 225 | 1.1528 |
| 1.1052 | 3.3333 | 250 | 1.1412 |
| 1.0614 | 3.6667 | 275 | 1.1329 |
| 1.1106 | 4.0 | 300 | 1.1271 |
| 1.1019 | 4.3333 | 325 | 1.1228 |
| 1.0691 | 4.6667 | 350 | 1.1212 |
| 1.0947 | 5.0 | 375 | 1.1153 |
| 1.0689 | 5.3333 | 400 | 1.1134 |
| 1.0598 | 5.6667 | 425 | 1.1116 |
| 1.0459 | 6.0 | 450 | 1.1111 |
| 1.0518 | 6.3333 | 475 | 1.1097 |
| 1.045 | 6.6667 | 500 | 1.1092 |
| 1.0658 | 7.0 | 525 | 1.1066 |
| 1.0706 | 7.3333 | 550 | 1.1067 |
| 1.0514 | 7.6667 | 575 | 1.1057 |
| 1.0412 | 8.0 | 600 | 1.1063 |
| 1.0455 | 8.3333 | 625 | 1.1052 |
| 0.9657 | 8.6667 | 650 | 1.1057 |
| 1.1015 | 9.0 | 675 | 1.1052 |
| 1.0294 | 9.3333 | 700 | 1.1051 |
| 1.0399 | 9.6667 | 725 | 1.1052 |
| 1.1125 | 10.0 | 750 | 1.1047 |
| 1.0219 | 10.3333 | 775 | 1.1046 |
| 0.9862 | 10.6667 | 800 | 1.1048 |
| 1.0682 | 11.0 | 825 | 1.1049 |
| 1.0587 | 11.3333 | 850 | 1.1049 |
| 1.0217 | 11.6667 | 875 | 1.1051 |
| 1.0547 | 12.0 | 900 | 1.1047 |
| 1.0047 | 12.3333 | 925 | 1.1047 |
| 1.021 | 12.6667 | 950 | 1.1047 |
| 1.0528 | 13.0 | 975 | 1.1047 |
| 1.0385 | 13.3333 | 1000 | 1.1047 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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