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---
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_steps_5k
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_sparse_80_percent_pretraining_warmup_20K_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: 0.7590
## 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: 6
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- total_eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2712 | 0.05 | 50 | 1.2374 |
| 1.0533 | 0.1 | 100 | 1.0529 |
| 0.9603 | 0.15 | 150 | 0.9668 |
| 0.9102 | 0.19 | 200 | 0.9145 |
| 0.8754 | 0.24 | 250 | 0.8775 |
| 0.8514 | 0.29 | 300 | 0.8503 |
| 0.8417 | 0.34 | 350 | 0.8298 |
| 0.8217 | 0.39 | 400 | 0.8146 |
| 0.8019 | 0.44 | 450 | 0.8026 |
| 0.7902 | 0.48 | 500 | 0.7914 |
| 0.7856 | 0.53 | 550 | 0.7819 |
| 0.7599 | 0.58 | 600 | 0.7734 |
| 0.7646 | 0.63 | 650 | 0.7689 |
| 0.7542 | 0.68 | 700 | 0.7635 |
| 0.7529 | 0.73 | 750 | 0.7581 |
| 0.7594 | 0.78 | 800 | 0.7533 |
| 0.7489 | 0.82 | 850 | 0.7493 |
| 0.7494 | 0.87 | 900 | 0.7452 |
| 0.7441 | 0.92 | 950 | 0.7472 |
| 0.7467 | 0.97 | 1000 | 0.7442 |
| 0.728 | 1.02 | 1050 | 0.7413 |
| 0.7263 | 1.07 | 1100 | 0.7384 |
| 0.7206 | 1.11 | 1150 | 0.7362 |
| 0.7223 | 1.16 | 1200 | 0.7343 |
| 0.7362 | 1.21 | 1250 | 0.7421 |
| 0.7374 | 1.26 | 1300 | 0.7401 |
| 0.7284 | 1.31 | 1350 | 0.7378 |
| 0.7309 | 1.36 | 1400 | 0.7356 |
| 0.724 | 1.41 | 1450 | 0.7339 |
| 0.72 | 1.45 | 1500 | 0.7317 |
| 0.73 | 1.5 | 1550 | 0.7509 |
| 0.7464 | 1.55 | 1600 | 0.7489 |
| 0.742 | 1.6 | 1650 | 0.7461 |
| 0.7378 | 1.65 | 1700 | 0.7447 |
| 0.7328 | 1.7 | 1750 | 0.7433 |
| 0.7433 | 1.75 | 1800 | 0.7411 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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