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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_1e6rate_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_1e6rate_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: 1.7960
## 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-06
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.2167 | 0.3333 | 25 | 1.1865 |
| 0.9806 | 0.6667 | 50 | 0.9618 |
| 0.936 | 1.0 | 75 | 0.9371 |
| 0.8294 | 1.3333 | 100 | 0.9512 |
| 0.8273 | 1.6667 | 125 | 0.9369 |
| 0.7851 | 2.0 | 150 | 0.9036 |
| 0.5263 | 2.3333 | 175 | 0.9990 |
| 0.5512 | 2.6667 | 200 | 0.9589 |
| 0.5272 | 3.0 | 225 | 0.9576 |
| 0.2888 | 3.3333 | 250 | 1.1371 |
| 0.2968 | 3.6667 | 275 | 1.1164 |
| 0.3381 | 4.0 | 300 | 1.1144 |
| 0.1802 | 4.3333 | 325 | 1.1697 |
| 0.2025 | 4.6667 | 350 | 1.1946 |
| 0.2273 | 5.0 | 375 | 1.2614 |
| 0.1417 | 5.3333 | 400 | 1.3260 |
| 0.1524 | 5.6667 | 425 | 1.3343 |
| 0.136 | 6.0 | 450 | 1.3735 |
| 0.117 | 6.3333 | 475 | 1.3843 |
| 0.1284 | 6.6667 | 500 | 1.3742 |
| 0.1172 | 7.0 | 525 | 1.4114 |
| 0.0905 | 7.3333 | 550 | 1.5000 |
| 0.1027 | 7.6667 | 575 | 1.5142 |
| 0.097 | 8.0 | 600 | 1.4912 |
| 0.0837 | 8.3333 | 625 | 1.5974 |
| 0.0832 | 8.6667 | 650 | 1.6185 |
| 0.0781 | 9.0 | 675 | 1.6203 |
| 0.0698 | 9.3333 | 700 | 1.6833 |
| 0.0722 | 9.6667 | 725 | 1.6960 |
| 0.0681 | 10.0 | 750 | 1.7139 |
| 0.0635 | 10.3333 | 775 | 1.7732 |
| 0.0654 | 10.6667 | 800 | 1.7704 |
| 0.0663 | 11.0 | 825 | 1.7647 |
| 0.0604 | 11.3333 | 850 | 1.7840 |
| 0.0628 | 11.6667 | 875 | 1.7916 |
| 0.0627 | 12.0 | 900 | 1.7947 |
| 0.061 | 12.3333 | 925 | 1.7962 |
| 0.062 | 12.6667 | 950 | 1.7967 |
| 0.0607 | 13.0 | 975 | 1.7960 |
| 0.0605 | 13.3333 | 1000 | 1.7960 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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