Chris Alexiuk
ai-maker-space/mistral-7b-instruct-tune-500s
e050268 verified
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral7b_instruct_generation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mistral7b_instruct_generation
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8004
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.03
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.857 | 0.0 | 20 | 1.8252 |
| 1.9363 | 0.01 | 40 | 1.7948 |
| 1.7643 | 0.01 | 60 | 1.7910 |
| 1.861 | 0.01 | 80 | 1.7915 |
| 1.8702 | 0.01 | 100 | 1.7903 |
| 1.8619 | 0.02 | 120 | 1.7905 |
| 1.7669 | 0.02 | 140 | 1.7956 |
| 1.8062 | 0.02 | 160 | 1.7895 |
| 1.7802 | 0.03 | 180 | 1.7958 |
| 1.7773 | 0.03 | 200 | 1.7855 |
| 1.8692 | 0.03 | 220 | 1.7936 |
| 1.7815 | 0.03 | 240 | 1.7939 |
| 1.8642 | 0.04 | 260 | 1.7990 |
| 1.8715 | 0.04 | 280 | 1.7953 |
| 1.8999 | 0.04 | 300 | 1.7999 |
| 1.7691 | 0.04 | 320 | 1.7919 |
| 1.7743 | 0.05 | 340 | 1.7973 |
| 1.7692 | 0.05 | 360 | 1.7919 |
| 1.954 | 0.05 | 380 | 1.7934 |
| 1.8872 | 0.06 | 400 | 1.7966 |
| 1.8925 | 0.06 | 420 | 1.7942 |
| 1.8384 | 0.06 | 440 | 1.7949 |
| 1.825 | 0.06 | 460 | 1.7982 |
| 1.8151 | 0.07 | 480 | 1.7959 |
| 1.8599 | 0.07 | 500 | 1.8004 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0