---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: sparse_mistral_7b_refined_web_50p_2024-04-13
  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. -->

# sparse_mistral_7b_refined_web_50p_2024-04-13

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2023

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 4
- seed: 0
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1350

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3391        | 0.01  | 25   | 2.4196          |
| 2.2711        | 0.02  | 50   | 2.3577          |
| 2.3054        | 0.02  | 75   | 2.3158          |
| 2.2795        | 0.03  | 100  | 2.2966          |
| 2.3175        | 0.04  | 125  | 2.2846          |
| 2.2388        | 0.05  | 150  | 2.2766          |
| 2.1679        | 0.06  | 175  | 2.2705          |
| 2.2996        | 0.06  | 200  | 2.2678          |
| 2.2788        | 0.07  | 225  | 2.2647          |
| 2.2448        | 0.08  | 250  | 2.2637          |
| 2.1837        | 0.09  | 275  | 2.2624          |
| 2.2089        | 0.1   | 300  | 2.2621          |
| 2.2686        | 0.1   | 325  | 2.2601          |
| 2.2254        | 0.11  | 350  | 2.2593          |
| 2.162         | 0.12  | 375  | 2.2590          |
| 2.2687        | 0.13  | 400  | 2.2563          |
| 2.2595        | 0.14  | 425  | 2.2571          |
| 2.186         | 0.14  | 450  | 2.2564          |
| 2.2689        | 0.15  | 475  | 2.2580          |
| 2.2472        | 0.16  | 500  | 2.2554          |
| 2.2005        | 0.17  | 525  | 2.2553          |
| 2.1983        | 0.18  | 550  | 2.2552          |
| 2.2388        | 0.18  | 575  | 2.2547          |
| 2.1443        | 0.19  | 600  | 2.2555          |
| 2.2198        | 0.2   | 625  | 2.2534          |
| 2.3008        | 0.21  | 650  | 2.2536          |
| 2.179         | 0.22  | 675  | 2.2521          |
| 2.2069        | 0.22  | 700  | 2.2531          |
| 2.1819        | 0.23  | 725  | 2.2526          |
| 2.1218        | 0.24  | 750  | 2.2536          |
| 2.1845        | 0.25  | 775  | 2.2515          |
| 2.2167        | 0.26  | 800  | 2.2510          |
| 2.2252        | 0.26  | 825  | 2.2520          |
| 2.1664        | 0.27  | 850  | 2.2519          |
| 2.1853        | 0.28  | 875  | 2.2530          |
| 2.1499        | 0.29  | 900  | 2.2513          |
| 2.2763        | 0.3   | 925  | 2.2517          |
| 2.2528        | 0.3   | 950  | 2.2518          |
| 2.2505        | 0.31  | 975  | 2.2500          |
| 2.1683        | 0.32  | 1000 | 2.2502          |
| 2.2177        | 0.33  | 1025 | 2.2501          |
| 2.238         | 0.34  | 1050 | 2.2516          |
| 2.193         | 0.34  | 1075 | 2.2507          |
| 2.2025        | 0.35  | 1100 | 2.2502          |
| 2.0944        | 0.36  | 1125 | 2.2512          |
| 2.2272        | 0.37  | 1150 | 2.2508          |
| 2.2264        | 0.38  | 1175 | 2.2500          |
| 2.1837        | 0.38  | 1200 | 2.2507          |
| 2.1444        | 0.39  | 1225 | 2.2489          |
| 2.2464        | 0.4   | 1250 | 2.2499          |
| 2.1398        | 0.41  | 1275 | 2.2512          |
| 2.1929        | 0.42  | 1300 | 2.2502          |
| 2.2384        | 0.42  | 1325 | 2.2498          |
| 2.223         | 0.43  | 1350 | 2.2481          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0