transformers safetensors sparse_mistral text-generation generated_from_trainer custom_code base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 autotrain_compatible region:us
---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral_Sparse_refined_web_90p_2024-02-16
  results: []
---

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# Mistral_Sparse_refined_web_90p_2024-02-16

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: 2.3570

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.7348        | 0.0   | 25   | 8.3850          |
| 5.9261        | 0.01  | 50   | 5.5212          |
| 3.6159        | 0.01  | 75   | 3.6689          |
| 3.0291        | 0.02  | 100  | 3.1644          |
| 2.786         | 0.02  | 125  | 2.9872          |
| 2.7951        | 0.02  | 150  | 2.9148          |
| 2.6959        | 0.03  | 175  | 2.8528          |
| 2.6134        | 0.03  | 200  | 2.8111          |
| 2.6439        | 0.04  | 225  | 2.7811          |
| 2.6326        | 0.04  | 250  | 2.7534          |
| 2.5528        | 0.04  | 275  | 2.7384          |
| 2.5601        | 0.05  | 300  | 2.7239          |
| 2.5693        | 0.05  | 325  | 2.7181          |
| 2.3934        | 0.06  | 350  | 2.7019          |
| 2.5466        | 0.06  | 375  | 2.6918          |
| 2.5872        | 0.06  | 400  | 2.6840          |
| 2.5638        | 0.07  | 425  | 2.6768          |
| 2.5235        | 0.07  | 450  | 2.6671          |
| 2.4179        | 0.08  | 475  | 2.6622          |
| 2.4862        | 0.08  | 500  | 2.6619          |
| 2.5594        | 0.08  | 525  | 2.6584          |
| 2.4604        | 0.09  | 550  | 2.6564          |
| 2.5887        | 0.09  | 575  | 2.6493          |
| 2.3974        | 0.1   | 600  | 2.6447          |
| 2.4769        | 0.1   | 625  | 2.6457          |
| 2.53          | 0.1   | 650  | 2.6317          |
| 2.5403        | 0.11  | 675  | 2.6341          |
| 2.4764        | 0.11  | 700  | 2.6296          |
| 2.489         | 0.12  | 725  | 2.6268          |
| 2.3969        | 0.12  | 750  | 2.6288          |
| 2.4164        | 0.12  | 775  | 2.6264          |
| 2.5208        | 0.13  | 800  | 2.6227          |
| 2.4997        | 0.13  | 825  | 2.6190          |
| 2.4853        | 0.14  | 850  | 2.6200          |
| 2.3447        | 0.14  | 875  | 2.6091          |
| 2.4384        | 0.14  | 900  | 2.6132          |
| 2.3863        | 0.15  | 925  | 2.6152          |
| 2.5076        | 0.15  | 950  | 2.6114          |
| 2.4299        | 0.16  | 975  | 2.6144          |
| 2.478         | 0.16  | 1000 | 2.6109          |


### Framework versions

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