transformers safetensors mistral text-generation generated_from_trainer dataset:openwebtext base_model:mistralai/Mistral-7B-Instruct-v0.1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- generated_from_trainer
datasets:
- openwebtext
model-index:
- name: sparse_sparse_80_percent_pretraining_warmup_20K_0_2_steps_5k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sparse_sparse_80_percent_pretraining_warmup_20K_0_2_steps_5k

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the openwebtext dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9832

## 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: 8
- eval_batch_size: 16
- seed: 0
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2964        | 0.02  | 50   | 1.2517          |
| 1.1086        | 0.05  | 100  | 1.0714          |
| 0.9727        | 0.07  | 150  | 0.9857          |
| 0.9326        | 0.1   | 200  | 0.9357          |
| 0.8944        | 0.12  | 250  | 0.8988          |
| 0.872         | 0.15  | 300  | 0.8700          |
| 0.8523        | 0.17  | 350  | 0.8516          |
| 0.8369        | 0.19  | 400  | 0.8358          |
| 0.8372        | 0.22  | 450  | 0.8226          |
| 0.8221        | 0.24  | 500  | 0.8116          |
| 0.8093        | 0.27  | 550  | 0.8020          |
| 0.804         | 0.29  | 600  | 0.7937          |
| 0.8111        | 0.32  | 650  | 0.7935          |
| 0.7949        | 0.34  | 700  | 0.7872          |
| 0.7947        | 0.36  | 750  | 0.7815          |
| 0.8045        | 0.39  | 800  | 0.7771          |
| 0.7706        | 0.41  | 850  | 0.7724          |
| 0.7669        | 0.44  | 900  | 0.7683          |
| 0.7691        | 0.46  | 950  | 0.7825          |
| 0.7737        | 0.48  | 1000 | 0.7779          |
| 0.7595        | 0.51  | 1050 | 0.7748          |
| 0.7672        | 0.53  | 1100 | 0.7709          |
| 0.7725        | 0.56  | 1150 | 0.7681          |
| 0.7551        | 0.58  | 1200 | 0.7658          |
| 0.8035        | 0.61  | 1250 | 0.8159          |
| 0.804         | 0.63  | 1300 | 0.8068          |
| 0.8074        | 0.65  | 1350 | 0.8016          |
| 0.7801        | 0.68  | 1400 | 0.7982          |
| 0.7842        | 0.7   | 1450 | 0.7951          |
| 0.7938        | 0.73  | 1500 | 0.7907          |
| 0.8625        | 0.75  | 1550 | 0.8568          |
| 0.8467        | 0.78  | 1600 | 0.8443          |
| 0.8216        | 0.8   | 1650 | 0.8379          |
| 0.8334        | 0.82  | 1700 | 0.8332          |
| 0.8287        | 0.85  | 1750 | 0.8292          |
| 0.8251        | 0.87  | 1800 | 0.8250          |
| 0.8969        | 0.9   | 1850 | 0.8790          |
| 0.8619        | 0.92  | 1900 | 0.8696          |
| 0.8566        | 0.95  | 1950 | 0.8645          |
| 0.8633        | 0.97  | 2000 | 0.8599          |
| 0.8622        | 0.99  | 2050 | 0.8558          |
| 0.8336        | 1.02  | 2100 | 0.8520          |
| 0.918         | 1.04  | 2150 | 0.9045          |
| 0.8755        | 1.07  | 2200 | 0.8960          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
