---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral_Sparse_refined_web_70p_2024-02-15
  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_2024-02-15

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: 2.2065

## 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: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0372        | 0.0   | 25   | 3.1256          |
| 2.6176        | 0.01  | 50   | 2.8951          |
| 2.5321        | 0.01  | 75   | 2.7409          |
| 2.4603        | 0.02  | 100  | 2.6753          |
| 2.4033        | 0.02  | 125  | 2.6424          |
| 2.4821        | 0.02  | 150  | 2.6147          |
| 2.4008        | 0.03  | 175  | 2.5858          |
| 2.3651        | 0.03  | 200  | 2.5688          |
| 2.3873        | 0.04  | 225  | 2.5565          |
| 2.4145        | 0.04  | 250  | 2.5470          |
| 2.3295        | 0.04  | 275  | 2.5321          |
| 2.3458        | 0.05  | 300  | 2.5185          |
| 2.3587        | 0.05  | 325  | 2.5146          |
| 2.1873        | 0.06  | 350  | 2.5093          |
| 2.3502        | 0.06  | 375  | 2.5093          |
| 2.3837        | 0.06  | 400  | 2.5021          |
| 2.3747        | 0.07  | 425  | 2.4994          |
| 2.3292        | 0.07  | 450  | 2.4957          |
| 2.2438        | 0.08  | 475  | 2.4940          |
| 2.3102        | 0.08  | 500  | 2.4889          |
| 2.3791        | 0.08  | 525  | 2.4858          |
| 2.2743        | 0.09  | 550  | 2.4827          |
| 2.4148        | 0.09  | 575  | 2.4813          |
| 2.2115        | 0.1   | 600  | 2.4830          |
| 2.2963        | 0.1   | 625  | 2.4834          |
| 2.3762        | 0.1   | 650  | 2.4805          |
| 2.3657        | 0.11  | 675  | 2.4764          |
| 2.3219        | 0.11  | 700  | 2.4746          |
| 2.3166        | 0.12  | 725  | 2.4712          |
| 2.2193        | 0.12  | 750  | 2.4747          |
| 2.2629        | 0.12  | 775  | 2.4703          |
| 2.3504        | 0.13  | 800  | 2.4732          |
| 2.3523        | 0.13  | 825  | 2.4662          |
| 2.3362        | 0.14  | 850  | 2.4645          |
| 2.202         | 0.14  | 875  | 2.4659          |
| 2.2795        | 0.14  | 900  | 2.4682          |
| 2.2254        | 0.15  | 925  | 2.4621          |
| 2.3507        | 0.15  | 950  | 2.4642          |
| 2.2825        | 0.16  | 975  | 2.4624          |
| 2.3301        | 0.16  | 1000 | 2.4603          |


### Framework versions

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