---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral_Sparse_refined_web_50p_2024-03-22
  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_50p_2024-03-22

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: 2.1289

## 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: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 12
- total_eval_batch_size: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1251

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4177        | 0.0   | 25   | 2.6401          |
| 2.5407        | 0.01  | 50   | 2.5820          |
| 2.3887        | 0.01  | 75   | 2.5299          |
| 2.2849        | 0.01  | 100  | 2.4991          |
| 2.2042        | 0.01  | 125  | 2.4802          |
| 2.2574        | 0.02  | 150  | 2.4609          |
| 2.2353        | 0.02  | 175  | 2.4473          |
| 2.3355        | 0.02  | 200  | 2.4449          |
| 2.3044        | 0.03  | 225  | 2.4381          |
| 2.2664        | 0.03  | 250  | 2.4348          |
| 2.1999        | 0.03  | 275  | 2.4263          |
| 2.2631        | 0.04  | 300  | 2.4247          |
| 2.2918        | 0.04  | 325  | 2.4184          |
| 2.1426        | 0.04  | 350  | 2.4185          |
| 2.149         | 0.04  | 375  | 2.4158          |
| 2.1937        | 0.05  | 400  | 2.4129          |
| 2.2372        | 0.05  | 425  | 2.4134          |
| 2.1997        | 0.05  | 450  | 2.4123          |
| 2.2937        | 0.06  | 475  | 2.4086          |
| 2.3067        | 0.06  | 500  | 2.4052          |
| 2.312         | 0.06  | 525  | 2.4060          |
| 2.257         | 0.07  | 550  | 2.4056          |
| 2.2729        | 0.07  | 575  | 2.4051          |
| 2.1952        | 0.07  | 600  | 2.4065          |
| 2.1225        | 0.07  | 625  | 2.3999          |
| 2.2168        | 0.08  | 650  | 2.4039          |
| 2.1682        | 0.08  | 675  | 2.4006          |
| 2.3027        | 0.08  | 700  | 2.4028          |
| 2.2077        | 0.09  | 725  | 2.4006          |
| 2.2119        | 0.09  | 750  | 2.3980          |
| 2.2539        | 0.09  | 775  | 2.3997          |
| 2.1323        | 0.1   | 800  | 2.3973          |
| 2.3612        | 0.1   | 825  | 2.4018          |
| 2.1674        | 0.1   | 850  | 2.3991          |
| 2.4429        | 0.1   | 875  | 2.4005          |
| 2.2753        | 0.11  | 900  | 2.3941          |
| 2.2058        | 0.11  | 925  | 2.3968          |
| 2.261         | 0.11  | 950  | 2.3983          |
| 2.1146        | 0.12  | 975  | 2.3945          |
| 2.1637        | 0.12  | 1000 | 2.3920          |
| 2.1595        | 0.12  | 1025 | 2.3933          |
| 2.3698        | 0.13  | 1050 | 2.3932          |
| 2.2472        | 0.13  | 1075 | 2.3914          |
| 2.2437        | 0.13  | 1100 | 2.3902          |
| 2.2625        | 0.13  | 1125 | 2.3911          |
| 2.2165        | 0.14  | 1150 | 2.3881          |
| 2.1428        | 0.14  | 1175 | 2.3888          |
| 2.1683        | 0.14  | 1200 | 2.3908          |
| 2.1771        | 0.15  | 1225 | 2.3923          |
| 2.153         | 0.15  | 1250 | 2.3900          |


### Framework versions

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