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

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should probably proofread and complete it, then remove this comment. -->

# mixtral-8x7b-instruct-v0.1-english-to-hinglish-translation

This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8719
- Rouge Scores: {'rouge1': 93.54182106152926, 'rouge2': 86.05446823709033, 'rougeL': 88.96922992123118, 'rougeLsum': 93.53351107529416}
- Bleu Scores: [0.0005895581385084092, 0.0005810015690343468, 0.0005667645554887882, 0.0005509301891024064]
- Gen Len: 2047.998

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------:|:--------:|
| 0.9944        | 1.0   | 500  | 0.8572          | {'rouge1': 93.66433639177112, 'rouge2': 86.16312209617104, 'rougeL': 88.96569028246026, 'rougeLsum': 93.65082127462976} | [0.000581715028380836, 0.0005735131190908485, 0.000559640714092523, 0.0005441766968373427]   | 2047.998 |
| 0.6294        | 2.0   | 1000 | 0.8719          | {'rouge1': 93.54182106152926, 'rouge2': 86.05446823709033, 'rougeL': 88.96922992123118, 'rougeLsum': 93.53351107529416} | [0.0005895581385084092, 0.0005810015690343468, 0.0005667645554887882, 0.0005509301891024064] | 2047.998 |


### 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