---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mixtral-8x7B-v0.1
model-index:
- name: pawan2411/semMixtral-LoRA
  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. -->

# pawan2411/semMixtral-LoRA

This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3446

## 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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4717        | 0.1   | 25   | 1.4328          |
| 1.409         | 0.2   | 50   | 1.3987          |
| 1.4058        | 0.3   | 75   | 1.3804          |
| 1.3436        | 0.4   | 100  | 1.3703          |
| 1.3548        | 0.5   | 125  | 1.3611          |
| 1.32          | 0.6   | 150  | 1.3558          |
| 1.3892        | 0.7   | 175  | 1.3509          |
| 1.384         | 0.8   | 200  | 1.3483          |
| 1.3442        | 0.89  | 225  | 1.3467          |
| 1.3692        | 0.99  | 250  | 1.3461          |
| 1.2944        | 1.09  | 275  | 1.3448          |
| 1.3064        | 1.19  | 300  | 1.3446          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0