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---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: HuggingFaceH4/zephyr-7b-beta
model-index:
- name: ft-HuggingFaceH4-zephyr-7b-beta-qlora-v3
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. -->
# ft-HuggingFaceH4-zephyr-7b-beta-qlora-v3
This model is a fine-tuned version of [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2700
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.566 | 2.5 | 5 | 1.3026 |
| 1.1359 | 5.0 | 10 | 1.2779 |
| 0.9114 | 7.5 | 15 | 1.3987 |
| 0.5972 | 10.0 | 20 | 1.4944 |
| 0.2936 | 12.5 | 25 | 1.8476 |
| 0.1104 | 15.0 | 30 | 2.1923 |
| 0.0311 | 17.5 | 35 | 2.5907 |
| 0.0168 | 20.0 | 40 | 2.7176 |
| 0.0132 | 22.5 | 45 | 2.8310 |
| 0.0115 | 25.0 | 50 | 2.9147 |
| 0.0106 | 27.5 | 55 | 3.0155 |
| 0.0103 | 30.0 | 60 | 3.1027 |
| 0.0101 | 32.5 | 65 | 3.1541 |
| 0.0099 | 35.0 | 70 | 3.1883 |
| 0.0097 | 37.5 | 75 | 3.2104 |
| 0.0095 | 40.0 | 80 | 3.2204 |
| 0.0094 | 42.5 | 85 | 3.2407 |
| 0.0095 | 45.0 | 90 | 3.2554 |
| 0.0093 | 47.5 | 95 | 3.2661 |
| 0.0094 | 50.0 | 100 | 3.2700 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |