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---
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
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