---
license: llama2
base_model: TheBloke/vigogne-2-70B-chat-GPTQ
tags:
- generated_from_trainer
model-index:
- name: Vigogne70b-last_fan
  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. -->

# Vigogne70b-last_fan

This model is a fine-tuned version of [TheBloke/vigogne-2-70B-chat-GPTQ](https://huggingface.co/TheBloke/vigogne-2-70B-chat-GPTQ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7698

## 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: 0.0004
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.01  | 50   | 1.0362          |
| No log        | 0.02  | 100  | 0.9411          |
| No log        | 0.03  | 150  | 0.9255          |
| No log        | 0.04  | 200  | 0.8966          |
| No log        | 0.05  | 250  | 0.8685          |
| No log        | 0.06  | 300  | 0.8707          |
| No log        | 0.08  | 350  | 0.8515          |
| No log        | 0.09  | 400  | 0.8420          |
| No log        | 0.1   | 450  | 0.8399          |
| 0.9406        | 0.11  | 500  | 0.8246          |
| 0.9406        | 0.12  | 550  | 0.8070          |
| 0.9406        | 0.13  | 600  | 0.8089          |
| 0.9406        | 0.14  | 650  | 0.8018          |
| 0.9406        | 0.15  | 700  | 0.7947          |
| 0.9406        | 0.16  | 750  | 0.7910          |
| 0.9406        | 0.17  | 800  | 0.7828          |
| 0.9406        | 0.18  | 850  | 0.7774          |
| 0.9406        | 0.19  | 900  | 0.7747          |
| 0.9406        | 0.21  | 950  | 0.7712          |
| 0.7812        | 0.22  | 1000 | 0.7698          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0