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---
base_model: t-bank-ai/T-lite-instruct-0.1
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: tmp
results: []
license: apache-2.0
datasets:
- Vikhrmodels/Grounded-RAG-RU-v2
---
<!-- 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. -->
# tmp
This model is a fine-tuned version of [t-bank-ai/T-lite-instruct-0.1](https://huggingface.co./t-bank-ai/T-lite-instruct-0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0736
## 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: 8e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3
- training_steps: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0658 | 0.0002 | 1 | 1.0817 |
| 0.9432 | 0.0004 | 2 | 1.0814 |
| 1.1006 | 0.0006 | 3 | 1.0809 |
| 0.8838 | 0.0008 | 4 | 1.0801 |
| 1.1528 | 0.0010 | 5 | 1.0793 |
| 0.8889 | 0.0012 | 6 | 1.0786 |
| 1.1655 | 0.0014 | 7 | 1.0780 |
| 1.0079 | 0.0016 | 8 | 1.0774 |
| 1.1685 | 0.0018 | 9 | 1.0768 |
| 1.1659 | 0.0020 | 10 | 1.0763 |
| 1.1395 | 0.0022 | 11 | 1.0758 |
| 0.9426 | 0.0024 | 12 | 1.0753 |
| 0.9772 | 0.0026 | 13 | 1.0750 |
| 1.3758 | 0.0028 | 14 | 1.0746 |
| 0.7022 | 0.0030 | 15 | 1.0743 |
| 1.5761 | 0.0032 | 16 | 1.0741 |
| 1.2847 | 0.0034 | 17 | 1.0739 |
| 1.1528 | 0.0036 | 18 | 1.0737 |
| 0.8362 | 0.0038 | 19 | 1.0736 |
| 0.9096 | 0.0040 | 20 | 1.0736 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0 |