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---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: ZeroShot-3.3.24-Mistral-7b-Multilanguage-3.2.0
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. -->
# ZeroShot-3.3.24-Mistral-7b-Multilanguage-3.2.0
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: 0.1109
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1175 | 0.06 | 100 | 0.1109 |
| 0.117 | 0.12 | 200 | 0.1318 |
| 0.1596 | 0.19 | 300 | 0.1316 |
| 0.4487 | 0.25 | 400 | 0.2081 |
| 1.0524 | 0.31 | 500 | 7.3647 |
| 0.0 | 0.37 | 600 | nan |
| 0.0 | 0.43 | 700 | nan |
| 0.0 | 0.5 | 800 | nan |
| 0.0 | 0.56 | 900 | nan |
| 0.0 | 0.62 | 1000 | nan |
| 0.0 | 0.68 | 1100 | nan |
| 0.0 | 0.74 | 1200 | nan |
| 0.0 | 0.81 | 1300 | nan |
| 0.0 | 0.87 | 1400 | nan |
| 0.0 | 0.93 | 1500 | nan |
| 0.0 | 0.99 | 1600 | nan |
| 0.0 | 1.05 | 1700 | nan |
| 0.0 | 1.12 | 1800 | nan |
| 9.5008 | 1.18 | 1900 | nan |
| 0.0 | 1.24 | 2000 | nan |
| 0.0 | 1.3 | 2100 | nan |
| 0.0 | 1.36 | 2200 | nan |
| 0.0 | 1.43 | 2300 | nan |
| 0.0 | 1.49 | 2400 | nan |
| 0.0 | 1.55 | 2500 | nan |
| 0.0 | 1.61 | 2600 | nan |
| 0.0 | 1.67 | 2700 | nan |
| 0.0 | 1.74 | 2800 | nan |
| 0.0 | 1.8 | 2900 | nan |
| 0.0 | 1.86 | 3000 | nan |
| 0.0 | 1.92 | 3100 | nan |
| 0.0 | 1.98 | 3200 | nan |
| 0.0 | 2.05 | 3300 | nan |
| 0.0 | 2.11 | 3400 | nan |
| 0.0 | 2.17 | 3500 | nan |
| 0.0 | 2.23 | 3600 | nan |
| 0.0 | 2.29 | 3700 | nan |
| 0.0 | 2.36 | 3800 | nan |
| 0.0 | 2.42 | 3900 | nan |
| 0.0 | 2.48 | 4000 | nan |
| 0.0 | 2.54 | 4100 | nan |
| 0.0 | 2.6 | 4200 | nan |
| 0.0 | 2.67 | 4300 | nan |
| 0.0 | 2.73 | 4400 | nan |
| 0.0 | 2.79 | 4500 | nan |
| 0.0 | 2.85 | 4600 | nan |
| 0.0 | 2.91 | 4700 | nan |
| 0.0 | 2.98 | 4800 | nan |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |