peft safetensors generated_from_trainer base_model:mistralai/Mixtral-8x7B-v0.1 base_model:adapter:mistralai/Mixtral-8x7B-v0.1 license:apache-2.0 region:us
---
base_model: mistralai/Mixtral-8x7B-v0.1
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: mixtral-8x7b-v0.1-english-to-hinglish-translation
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mixtral-8x7b-v0.1-english-to-hinglish-translation

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: 1.0769
- Rouge Scores: {'rouge1': 0.9045408202972536, 'rouge2': 0.795425441228359, 'rougeL': 0.8399846297860634, 'rougeLsum': 0.9043739034131012}
- Bleu Scores: [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873]
- Gen Len: 2048.0

## 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: 0.0001
- 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: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                            | Bleu Scores                                                                                   | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------:|:--------:|
| 1.1771        | 1.0   | 500  | 1.0579          | {'rouge1': 0.9070255400902434, 'rouge2': 0.7976770190068221, 'rougeL': 0.8400261479965636, 'rougeLsum': 0.9069363147075731} | [0.00028395954091190866, 0.0002796973368739713, 0.0002722057765709132, 0.000263740024418467]  | 2047.996 |
| 0.7788        | 2.0   | 1000 | 1.0769          | {'rouge1': 0.90.45408202972536, 'rouge2': 0.795425441228359, 'rougeL': 0.8399846297860634, 'rougeLsum': 0.9043739034131012}  | [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873] | 2048.0   |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.16.2.dev0
- Tokenizers 0.15.1