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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/zephyr-7B-alpha-GPTQ
model-index:
- name: zephyr-chatbot
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. -->
# zephyr-chatbot
This model is a fine-tuned version of [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8794
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: gptq
- bits: 4
- tokenizer: None
- dataset: None
- group_size: 128
- damp_percent: 0.1
- desc_act: True
- sym: True
- true_sequential: True
- use_cuda_fp16: False
- model_seqlen: 4095
- block_name_to_quantize: model.layers
- module_name_preceding_first_block: ['model.embed_tokens']
- batch_size: 1
- pad_token_id: None
- use_exllama: False
- max_input_length: None
- exllama_config: {'version': <ExllamaVersion.ONE: 1>}
- cache_block_outputs: True
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9364 | 1.0 | 121 | 0.9402 |
| 0.8289 | 2.0 | 242 | 0.8849 |
| 0.7249 | 3.0 | 363 | 0.8540 |
| 0.6322 | 4.0 | 484 | 0.8387 |
| 0.5337 | 5.0 | 605 | 0.8475 |
| 0.4523 | 6.0 | 726 | 0.8586 |
| 0.405 | 7.0 | 847 | 0.8698 |
| 0.3965 | 8.0 | 968 | 0.8794 |
| 0.3859 | 8.26 | 1000 | 0.8794 |
### Framework versions
- PEFT 0.7.0
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0 |