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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_2024-02-16
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_2024-02-16
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: 2.1260
## 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: 3
- total_train_batch_size: 9
- total_eval_batch_size: 3
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5975 | 0.01 | 25 | 2.6362 |
| 2.3082 | 0.01 | 50 | 2.5659 |
| 2.4024 | 0.02 | 75 | 2.5151 |
| 2.3358 | 0.02 | 100 | 2.4817 |
| 2.2267 | 0.03 | 125 | 2.4660 |
| 2.271 | 0.04 | 150 | 2.4456 |
| 2.1709 | 0.04 | 175 | 2.4413 |
| 2.2549 | 0.05 | 200 | 2.4306 |
| 2.2536 | 0.05 | 225 | 2.4243 |
| 2.2234 | 0.06 | 250 | 2.4212 |
| 2.2516 | 0.07 | 275 | 2.4202 |
| 2.2827 | 0.07 | 300 | 2.4146 |
| 2.1774 | 0.08 | 325 | 2.4156 |
| 2.278 | 0.08 | 350 | 2.4094 |
| 2.204 | 0.09 | 375 | 2.4088 |
| 2.1987 | 0.1 | 400 | 2.4073 |
| 2.1985 | 0.1 | 425 | 2.4041 |
| 2.2198 | 0.11 | 450 | 2.4069 |
| 2.2555 | 0.11 | 475 | 2.4014 |
| 2.1567 | 0.12 | 500 | 2.4017 |
| 2.2918 | 0.13 | 525 | 2.3998 |
| 2.2559 | 0.13 | 550 | 2.3959 |
| 2.2234 | 0.14 | 575 | 2.3978 |
| 2.2001 | 0.14 | 600 | 2.3944 |
| 2.1409 | 0.15 | 625 | 2.3957 |
| 2.2034 | 0.16 | 650 | 2.3981 |
| 2.1863 | 0.16 | 675 | 2.3941 |
| 2.2372 | 0.17 | 700 | 2.3936 |
| 2.2438 | 0.17 | 725 | 2.3953 |
| 2.2172 | 0.18 | 750 | 2.3943 |
| 2.1917 | 0.19 | 775 | 2.3921 |
| 2.1137 | 0.19 | 800 | 2.3912 |
| 2.0766 | 0.07 | 825 | 2.3935 |
| 2.1926 | 0.08 | 850 | 2.3913 |
| 2.2948 | 0.08 | 875 | 2.3915 |
| 2.1349 | 0.08 | 900 | 2.3917 |
| 2.2446 | 0.08 | 925 | 2.3876 |
| 2.253 | 0.09 | 950 | 2.3880 |
| 2.0729 | 0.09 | 975 | 2.3890 |
| 2.1965 | 0.09 | 1000 | 2.3873 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|