---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral_Sparse_refined_web_70p_2024-03-12
  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. -->

# Mistral_Sparse_refined_web_70p_2024-03-12

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: 2.1626

## 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: 1
- seed: 0
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7221        | 0.0   | 25   | 2.8218          |
| 2.4266        | 0.01  | 50   | 2.6972          |
| 2.4153        | 0.01  | 75   | 2.6181          |
| 2.3588        | 0.02  | 100  | 2.5695          |
| 2.3274        | 0.02  | 125  | 2.5427          |
| 2.4054        | 0.02  | 150  | 2.5244          |
| 2.3274        | 0.03  | 175  | 2.5144          |
| 2.3042        | 0.03  | 200  | 2.4995          |
| 2.3296        | 0.04  | 225  | 2.4898          |
| 2.3621        | 0.04  | 250  | 2.4844          |
| 2.2825        | 0.04  | 275  | 2.4756          |
| 2.2932        | 0.05  | 300  | 2.4704          |
| 2.3015        | 0.05  | 325  | 2.4693          |
| 2.139         | 0.06  | 350  | 2.4612          |
| 2.2953        | 0.06  | 375  | 2.4553          |
| 2.3358        | 0.06  | 400  | 2.4546          |
| 2.3302        | 0.07  | 425  | 2.4506          |
| 2.2814        | 0.07  | 450  | 2.4506          |
| 2.2014        | 0.08  | 475  | 2.4455          |
| 2.266         | 0.08  | 500  | 2.4434          |
| 2.3309        | 0.08  | 525  | 2.4430          |
| 2.2278        | 0.09  | 550  | 2.4417          |
| 2.3621        | 0.09  | 575  | 2.4384          |
| 2.1614        | 0.1   | 600  | 2.4385          |
| 2.2504        | 0.1   | 625  | 2.4370          |
| 2.3301        | 0.1   | 650  | 2.4350          |
| 2.3177        | 0.11  | 675  | 2.4331          |
| 2.2784        | 0.11  | 700  | 2.4307          |
| 2.2681        | 0.12  | 725  | 2.4305          |
| 2.1777        | 0.12  | 750  | 2.4314          |
| 2.2164        | 0.12  | 775  | 2.4321          |
| 2.3068        | 0.13  | 800  | 2.4292          |
| 2.3131        | 0.13  | 825  | 2.4267          |
| 2.2971        | 0.14  | 850  | 2.4256          |
| 2.1623        | 0.14  | 875  | 2.4231          |
| 2.2308        | 0.14  | 900  | 2.4246          |
| 2.1772        | 0.15  | 925  | 2.4259          |
| 2.3114        | 0.15  | 950  | 2.4226          |
| 2.2434        | 0.16  | 975  | 2.4268          |
| 2.2852        | 0.16  | 1000 | 2.4259          |
| 2.2924        | 0.16  | 1025 | 2.4262          |
| 2.3095        | 0.17  | 1050 | 2.4231          |
| 2.3378        | 0.17  | 1075 | 2.4225          |
| 2.265         | 0.18  | 1100 | 2.4181          |


### Framework versions

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